nils-herrmann/clean_scirepeval huggingface dataset:
A New Soft Pneumatic Elbow Pad for Joint Assistance With Application to Smart Campus

This paper presents an assistance equipment of human elbow joint, which aims to help patients who have elbow injury issues in smart campus environment. A new type of soft pneumatic elbow pad (SPEP) which adopted soft material manufacturing technology is presented. Compared with the rigid assistant equipment, the SPEP shows more comfort, smaller equipment size, and convenience of wearing. Meanwhile, three different types of sensors (the air pressure sensor, bending sensor, and force sensor) are used in the SPEP to discover the two important characteristics which are applied. In order to verify the effectiveness of the designed SPEP, two analysis methods are presented. The surface electromyogram signal and the root mean square analysis are used in the first method, which prove that the SPEP could reduce the activity of the muscle and assist power during the elbow movement. Compared with the first method, the second method which is the model of calculation after wearing SPEP can obtain specific value of assisting power in the biceps and olecranon. Thus, the aforementioned methods illustrate the feasibility of the SPEP. Finally, in order to make the SPEP used in daily life, a portable backpack with the control system and the energy system is applied to the field of human assistance equipment.
Blood pressure-lowering effect of Shinrin-yoku (Forest bathing): a systematic review and meta-analysis

Shinrin-yoku (experiencing the forest atmosphere or forest bathing) has received increasing attention from the perspective of preventive medicine in recent years. Some studies have reported that the forest environment decreases blood pressure. However, little is known about the possibility of anti-hypertensive applications of Shinrin-yoku. This study aimed to evaluate preventive or therapeutic effects of the forest environment on blood pressure.



We systematically reviewed the medical literature and performed a meta-analysis.Four electronic databases were systematically searched for the period before May 2016 with language restriction of English and Japanese. The review considered all published, randomized, controlled trials, cohort studies, and comparative studies that evaluated the effects of the forest environment on changes in systolic blood pressure. A subsequent meta-analysis was performed.



Twenty trials involving 732 participants were reviewed. Systolic blood pressure of the forest environment was significantly lower than that of the non-forest environment. Additionally, diastolic blood pressure of the forest environment was significantly lower than that of the non-forest environment.



This systematic review shows a significant effect of Shinrin-yoku on reduction of blood pressure.
Combining Lexicon-based and Learning-based Methods for Twitter Sentiment Analysis

With the booming of microblogs on the Web, people have begun to express their opinions on a wide variety of topics on Twitter and other similar services. Sentiment analysis on entities (e.g., products, organizations, people, etc.) in tweets (posts on Twitter) thus becomes a rapid and effective way of gauging public opinion for business marketing or social studies. However, Twitter's unique characteristics give rise to new problems for current sentiment analysis methods, which originally focused on large opinionated corpora such as product reviews. In this paper, we propose a new entity-level sentiment analysis method for Twitter. The method first adopts a lexiconbased approach to perform entity-level sentiment analysis. This method can give high precision, but low recall. To improve recall, additional tweets that are likely to be opinionated are identified automatically by exploiting the information in the result of the lexicon-based method. A classifier is then trained to assign polarities to the entities in the newly identified tweets. Instead of being labeled manually, the training examples are given by the lexicon-based approach. Experimental results show that the proposed method dramatically improves the recall and the F-score, and outperforms the state-of-the-art baselines. External Posting Date: June 21, 2011 [Fulltext] Approved for External Publication Internal Posting Date: June 21, 2011  Combining Lexicon-based and Learning-based Methods for Twitter Sentiment Analysis Lei Zhang, Riddhiman Ghosh, Mohamed Dekhil, Meichun Hsu,  Palo Alto, CA 851 S. Morgan St., Chicago, IL {riddhiman.ghosh, mohamed.dekhil, {lzhang3, liub}@cs.uic.edu meichun.hsu}@hp.com
Don't throw me away: Threats Caused by the Abandoned Internet Resources Used by Android Apps

This study aims to understand the threats caused by abandoned Internet resources used by Android apps. By abandoned, we mean Internet resources that support apps that were published and are still available on the mobile app marketplace, but have not been maintained and hence are at risk for abuse by an outsider. Internet resources include domain names and hard-coded IP addresses, which could be used for nefarious purposes, e.g., stealing sensitive private information, scamming and phishing, click fraud, and injecting malware distribution URL. As a result of the analysis of 1.1 M Android apps published in the official marketplace, we uncovered 3,628 of abandoned Internet resources associated with 7,331 available mobile apps. These resources are subject to hijack by outsiders. Of these apps, 13 apps have been installed more than a million of times, a measure of the breadth of the threat. Based on the findings of empirical experiments, we discuss potential threats caused by abandoned Internet resources and propose countermeasures against these threats.
NewsVallum: Semantics-Aware Text and Image Processing for Fake News Detection system

As a consequence of the social revolution we faced on the Web, news and information we daily enjoy may come from different and diverse sources which are not necessarily the traditional ones such as newspapers, either in their paper or online version, television, radio, etc. Everyone on the Web is allowed to produce and share news which can soon become viral if they follow the new media channels represented by social networks. This freedom in producing and sharing news comes with a counter-effect: the proliferation of fake news. Unfortunately, they can be very effective and may influence people and, more generally, the public opinion. We propose a combined approach of natural language and image processing that takes into account the semantics encoded within both text and images coming with news together with contextual information that may help in the classification of a news as fake or not.
A Package for Survival Analysis in S

3 Mathematical Backround 7 3.1 Survival . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7 3.1.1 Estimation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7 3.1.2 Variance . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8 3.1.3 Mean and median . . . . . . . . . . . . . . . . . . . . . . . . . . 9 3.2 Expected Survival . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10 3.2.1 Individual Expected Survival . . . . . . . . . . . . . . . . . . . . 10 3.2.2 Cohort expected survival . . . . . . . . . . . . . . . . . . . . . . 11 3.2.3 Approximations . . . . . . . . . . . . . . . . . . . . . . . . . . . . 14 3.2.4 Testing . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 14 3.3 Cox Model . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 16 3.3.1 Computation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 18 3.3.2 Residuals . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 19 3.3.3 Variance of the Residuals . . . . . . . . . . . . . . . . . . . . . . 20 3.3.4 Tied data . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 21 3.3.5 Tests for Proportional Hazards . . . . . . . . . . . . . . . . . . . 24 3.3.6 Robust Variance . . . . . . . . . . . . . . . . . . . . . . . . . . . 27 3.3.7 Weighted Cox models . . . . . . . . . . . . . . . . . . . . . . . . 32 3.3.8 Estimated survival . . . . . . . . . . . . . . . . . . . . . . . . . .
Multilevel Color Transfer on Images for Providing an Artistic Sight of the World

This paper represents a twofold approach. On the one hand, we introduce a simple method that encompasses an ensemble of image processing algorithms with a multilevel color transfer approach at its core. On the other hand, the method is applied for providing an artistic look to standard images. The approach proposes a multilevel color transfer in a chromatic channel of the CIELAB color space. Once converted from red, green and blue, a specific channel on both images, input and target (reference), is thresholded in a number of levels. Later, the color transfer is performed between regions from corresponding levels using a classical color transfer method. In the application phase, the color palette of a recognized artwork of the Fauve movement is mapped to the input image, emulating the sight of the artist, characterized by the use of vivid colors. Filtering techniques are applied to the outcome, in order to emulate the basic brushstrokes of the artist. Experimental results are shown, visualizing and comparing the input images with the outcomes.
A Systematic Review on the Suspicious Profiles Detection on Online Social Media Data

Escalating crimes on digital facet alarms the law enforcement bodies to keep a gaze on online activities which involve massive amount of data. This will raise a need to detect suspicious activities on online available social media data by optimizing investigations using data mining tools. This paper intends to throw some light on the data mining techniques which are designed and developed for closely examining social media data for suspicious activities and profiles in different domains. Additionally, this study will categorize the techniques under various groups highlighting their important features, challenges and application realm. Article history Received: 14 July 2017 Accepted:08 August 2017
A dexterous gripper for in-hand manipulation

During the last few decades, robotic grippers are developed by research community to solve grasping complexities of several objects as their primary objective. Due to the increasing demands of industries, many issues are rising and remain unsolved such as in-hand manipulation, placing object with appropriate posture. Operations like twisting, altering orientation of object, in a hand, requires significant dexterity of the gripper that must be achieved from a compact mechanical design at the first place. In this paper, a newly designed gripper is proposed whose primary goal is to solve in-hand manipulation. The gripper is derived from four identical finger modules; each module has four DOFs, consists of a five bar linkage to grasp and additional two DOFs mechanism similar to ball spline is conceived to manipulate object. Hence the easily constructible gripper is capable to grasp and manipulate plurality of object. As a preliminary inspection, an optimized platform that represents the central concept of the proposed gripper is developed, to the aim of evaluating kinematic feasibilities of manipulation of different objects.
"multilingual" Deep Neural Network for Music Genre Classification

Multilingual deep neural network (DNN) has been widely used in low-resource automatic speech recognition (ASR) in order to balance the rich-resource and low-resource speech recognition or to build the low-resource ASR system quickly. Inspired by the idea of using multilingual DNN for ASR, we use a “multilingual” DNN (Multi-DNN) for music genre classification. However, we do not have “multilingual” in music, so we use the similar resource instead. In order to obtain the similar resource corresponding to small target database, the nearest neighbor (NN) algorithm is used to relabel the large similar database. Then the re-labeled large similar database is used to train a Multi-DNN, and the small target database is used to further adapt the trained Multi-DNN. By using the Multi-DNN approach, the DNN can be well trained, and be transferred to the small target database quickly. The experiments are evaluated on the benchmark databases, ISMIR database and GTZAN database, which are used as the large similar database and small target database respectively. The experiment results show that the proposed method can achieve 93.4% (10-fold cross-validation) average classification accuracy on GTZAN database, which outperforms the state-ofthe-art best performance on this database.
New Compact CMOS Li-Ion Battery Charger Using Charge-Pump Technique for Portable Applications

This paper presents a new compact CMOS Li-Ion battery charger for portable applications that uses a charge-pump technique. The proposed charger features a small chip size and a simple circuit structure. Additionally, it provides basic functions with voltage/current detection, end-of-charge detection, and charging speed control. The charger operates in dual-mode and is supported in the trickle/large constant-current mode to constant-voltage mode with different charging rates. This charger is implemented using a TSMC 0.35-mum CMOS process with a 5-V power supply. The output voltage is almost 4.2 V, and the maximum charging current reaches 700 mA. It has 67.89% power efficiency, 837-mW chip power dissipation, and only 1.455times1.348 mm2 in chip area including pads
3D human face description: landmarks measures and geometrical features

Morphometric measures and geometrical features are widely used to descript faces. Generally, they are extracted punctually from landmarks, namely anthropometric reference points. The aims are various, such as face recognition, facial expression recognition, face detection, study of changes in facial morphology due to growth, or dysmorphologies. Most of the time, landmarks were extracted with the help of an algorithm or manually located on the faces. Then, measures are computed or geometrical features are extracted to perform the scope of the study.
An X-band 6-bit active phase shifter

This paper presents a 6-bit active phase shifter using a new vector-sum method for X-band (8-12 GHz) phased arrays in 0.13 μm SiGe BiCMOS process. An RC filter is used to generate two orthogonal vectors which are then fed into four VGAs, two using the common-base and two using the common-emitter topology. This generates 4 vectors of 0°, 90°, 180° and 270° which are scaled and added by varying the gains of the VGAs to generate any phase between 0-360°. The gains of the VGAs are adjusted with analog voltage control using the current-steering method. The outputs of the VGAs are connected together with a common load in order to add the vectors in current-domain. The phase shifter achieves <; 5.6° RMS phase error over 8-12 GHz and <; 3.1° RMS phase error over 9-11 GHz. The phase shifter has a power consumption of 16.6 mW from a 2V supply. The chip size is 850 μm × 532 μm including the probing pads. These performance parameters are comparable with the state of the art of the technology in literature.
Metaphor in the Mind : The Cognition of Metaphor

The most sustained and innovative recent work on metaphor has occurred in cognitive science and psychology. Psycholinguistic investigation suggests that novel, poetic metaphors are processed differently than literal speech, while relatively conventionalized and contextually salient metaphors are processed more like literal speech. This conflicts with the view of “cognitive linguists” like George Lakoff that all or nearly all thought is essentially metaphorical. There are currently four main cognitive models of metaphor comprehension: juxtaposition, category-transfer, feature-matching, and structural alignment. Structural alignment deals best with the widest range of examples; but it still fails to account for the complexity and richness of fairly novel, poetic metaphors. 1. General Issues in the Study of Metaphor Philosophers have often adopted a dismissive attitude toward metaphor. Hobbes (ch. 8) advocated excluding metaphors from rational discourse because they “openly profess deceit,” while Locke (Bk. 3, ch. 10) claimed that figurative uses of language serve only “to insinuate wrong ideas, move the passions, and thereby mislead the judgment; and so indeed are perfect cheats.” Later, logical positivists like Ayer and Carnap assumed that because metaphors like (1) How sweet the moonlight sleeps upon this bank!2 involve category mistakes, they have no real meaning or verification conditions. Thus, they too mentioned metaphor only to place it beyond the pale of rational discourse. Starting in the 1960s and 70s, philosophers and linguists began to take more positive interest in metaphor. Black argued forcefully that metaphors do have a distinctive, essentially non-propositional meaning or cognitive significance, which is produced by the “interaction” of the “systems of associated commonplaces” for the metaphor’s “primary” and “secondary” subjects (e.g., with moonlight and sleeping sweetly). Other theorists were more friendly to the idea that metaphorical and literal meaning are of the same essential kind. Many of them proposed that the literal absurdity of metaphors  Compass 1/2 (2006): 154–170, 10.1111/j.1747-9991.2006.00013.x
The integration of the internal and external milieu in the insula during dynamic emotional experiences

Whilst external events trigger emotional responses, interoception (the perception of internal physiological states) is fundamental to core emotional experience. By combining high resolution functional neuroimaging with concurrent physiological recordings, we investigated the neural mechanisms of interoceptive integration during free listening to an emotionally salient audio film. We found that cardiac activity, a key interoceptive signal, was robustly synchronised across participants and centrally represented in the posterior insula. Effective connectivity analysis revealed that the anterior insula, specifically tuned to the emotionally salient moments of the audio stream, serves as an integration hub of interoceptive processing: interoceptive states represented in the posterior insula are integrated with exteroceptive representations by the anterior insula to highlight these emotionally salient moments. Our study for the first time demonstrates the insular hierarchy for interoceptive processing during natural emotional experience. These findings provide an ecologically-valid framework for elucidating the neural underpinnings of emotional deficits in neuropsychiatric disorders.
Identification of extremist videos in online video sharing sites

Web 2.0 has become an effective grassroots communication platform for extremists to promote their ideas, share resources, and communicate among each other. As an important component of Web 2.0, online video sharing sites such as YouTube and Google video have also been utilized by extremist groups to distribute videos. This study presented a framework for identifying extremist videos in online video sharing sites by using user-generated text content such as comments, video descriptions, and titles without downloading the videos. Text features including lexical features, syntactic features and content specific features were first extracted. Then Information Gain was used for feature selection, and Support Vector Machine was deployed for classification. The exploratory experiment showed that our proposed framework is effective for identifying online extremist videos, with the F-measure as high as 82%.
Sentiment Analysis on Twitter Data

Now-a-days social networking sites are at the boom, so large amount of data is generated. Millions of people are sharing their views daily on micro blogging sites, since it contains short and simple expressions. In this paper, we will discuss about a paradigm to extract the sentiment from a famous micro blogging service, Twitter, where users post their opinions for everything. In this paper, we will discuss the existing analysis of twitter dataset with data mining approach such as use of Sentiment analysis algorithm using machine learning algorithms. An approach is introduced that automatically classifies the sentiments of Tweets taken from Twitter dataset as in . These messages or tweets are classified as positive, negative or neutral with respect to a query term. This is very useful for the companies who want to know the feedback about their product brands or the customers who want to search the opinion from others about product before purchase. We will use machine learning algorithms for classifying the sentiment of Twitter messages using distant supervision which is discussed in . The training data consists of Twitter messages with emoticons, acronyms which are used as noisy labels discussed in . We examine sentiment analysis on Twitter data. The contributions of this survey paper are: (1) we use Parts Of Speech (POS)-specific prior polarity features. (2) We also use a tree kernel to prevent the need for monotonous feature engineering.
Sentiment after Translation: A Case-Study on Arabic Social Media Posts

When text is translated from one language into another, sentiment is preserved to varying degrees. In this paper, we use Arabic social media posts as stand-in for source language text, and determine loss in sentiment predictability when they are translated into English, manually and automatically. As benchmarks, we use manually and automatically determined sentiment labels of the Arabic texts. We show that sentiment analysis of English translations of Arabic texts produces competitive results, w.r.t. Arabic sentiment analysis. We discover that even though translation significantly reduces the human ability to recover sentiment, automatic sentiment systems are still able to capture sentiment information from the translations.
The Digital Sin City: An Empirical Study of Craigslist's Impact on Prostitution Trends

Online prostitution has flourished due to presence of online intermediaries. Despite the illegality of selling sexual services online, the Section 230 of Communications Decency Act shields websites from liability for unlawful postings by third parties. Consequently, the websites like Craigslist have become a haven for prostitution-related ads. In this paper, we quantify the economic impact of Craigslist’s entry on prostitution incidence, and identify potential pathways in which the website affects the sex industry. Using a national panel data for 1,796 U.S. counties from 1999 to 2008, our results suggest that entry of Craigslist to a county is related to 26.61 percent increase in prostitution cases. In addition, our analyses investigates four key market mechanisms, namely the relationship to commercial vice, geographical trends, spillover effects, and enhanced policing efficacy. Our results contributes broadly to the emerging literature that researches the societal challenges associated with online intermediaries and Internet penetration.
Developing mindfulness in college students through movement-based courses: effects on self-regulatory self-efficacy, mood, stress, and sleep quality.

This study examined whether mindfulness increased through participation in movement-based courses and whether changes in self-regulatory self-efficacy, mood, and perceived stress mediated the relationship between increased mindfulness and better sleep.



166 college students enrolled in the 2007-2008 academic year in 15 week classes in Pilates, Taiji quan, or GYROKINESIS.



At beginning, middle, and end of the semester, participants completed measures of mindfulness, self-regulatory self-efficacy, mood, perceived stress, and sleep quality.



Total mindfulness scores and mindfulness subscales increased overall. Greater changes in mindfulness were directly related to better sleep quality at the end of the semester after adjusting for sleep disturbance at the beginning. Tiredness, Negative Arousal, Relaxation, and Perceived Stress mediated the effect of increased mindfulness on improved sleep.



Movement-based courses can increase mindfulness. Increased mindfulness accounts for changes in mood and perceived stress, which explain, in part, improved sleep quality.