nils-herrmann/clean_scirepeval huggingface dataset:
( Why ) Should We Use SEM ? Pros and Cons of Structural Equation Modeling

During the last two decades, Structural Equation Modeling (SEM) has evolved from a statistical technique for insiders to an established valuable tool for a broad scientific public. This class of analyses has much to offer, but at what price? This paper provides an overview on SEM, its underlying ideas, potential applications and current software. Furthermore, it discusses avoidable pitfalls as well as built-in drawbacks in order to lend support to researchers in deciding whether or not SEM should be integrated into their research tools. Commented findings of an internet survey give a “State of the Union Address” on SEM users and usage. Which kinds of models are preferred? Which software is favoured in current psychological research? In order to assist the reader on his first steps, a SEM first-aid kit is included. Typical problems and possible solutions are addressed, helping the reader to get the support he needs. Hence, the paper may assist the novice on the first steps and self-critically reminds the advanced reader of the limitations of Structural Equation Modeling
A Robust Blind Watermarking Using Convolutional Neural Network

This paper introduces a blind watermarking based on a convolutional neural network (CNN). We propose an iterative learning framework to secure robustness of watermarking. One loop of learning process consists of the following three stages: Watermark embedding, attack simulation, and weight update. We have learned a network that can detect a 1-bit message from a image sub-block. Experimental results show that this learned network is an extension of the frequency domain that is widely used in existing watermarking scheme. The proposed scheme achieved robustness against geometric and signal processing attacks with a learning time of one day.
Applications of Lie groups and Lie algebra to computer vision: A brief survey

Recent years an extensive literature appears using the Lie groups theory to solve the problems of computer vision. Lie groups theory is the natural representation of a space of transformations. Lie algebra is the tangent space of Lie groups at the identity. From Lie groups to Lie algebra, we can establish a mapping from the multiplicative structure to an equivalent vector space representation, which makes correlation calculation become rational and precise. Based on the linear structure of Lie algebra, many statistical learning methods can be readily applied. This survey briefly reviews the different approaches about the use of Lie groups theory that have been developed by research; introducing the mathematical background of Lie groups theory corresponding to computer vision; describing the main approaches in details according two categories.
Single-energy metal artifact reduction for helical computed tomography of the pelvis in patients with metal hip prostheses

To compare the quality of helical computed tomography (CT) images of the pelvis in patients with metal hip prostheses reconstructed using adaptive iterative dose reduction (AIDR) and AIDR with single-energy metal artifact reduction (SEMAR-A). This retrospective study included 28 patients (mean age, 64.6 ± 11.4 years; 6 men and 22 women). CT images were reconstructed using AIDR and SEMAR-A. Two radiologists evaluated the extent of metal artifacts and the depiction of structures in the pelvic region and looked for mass lesions. A radiologist placed a region of interest within the bladder and recorded CT attenuation. The metal artifacts were significantly reduced in SEMAR-A as compared to AIDR (p < 0.0001). The depictions of the bladder, ureter, prostate/uterus, rectum, and pelvic sidewall were significantly better with SEMAR-A than with AIDR (p < 0.02). All lesions were diagnosed with SEMAR-A, while some were not diagnosed with AIDR. The median and interquartile range (in parentheses) of CT attenuation within the bladder for AIDR were −34.0 (−46.6 to −15.0) Hounsfield units (HU) and were more variable than those seen for SEMAR-A [5.4 (−1.3 to 11.1)] HU (p = 0.033). In comparison with AIDR, SEMAR-A provided pelvic CT images of significantly better quality for patients with metal hip prostheses.
Absent nasal bone at 11-14 weeks of gestation and chromosomal defects.

To examine the association between absence of the nasal bone at the 11-14-week ultrasound scan and chromosomal defects.



Ultrasound examination was carried out in 3829 fetuses at 11-14 weeks' gestation immediately before fetal karyotyping. At the scan the fetal crown-rump length (CRL) and nuchal translucency (NT) thickness were measured and the fetal profile was examined for the presence or absence of the nasal bone. Maternal characteristics including ethnic origin were also recorded.



The fetal profile was successfully examined in 3788 (98.9%) cases. In 3358/3788 cases the fetal karyotype was normal and in 430 it was abnormal. In the chromosomally normal group the incidence of absent nasal bone was related firstly to the ethnic origin of the mother (2.8% for Caucasians, 10.4% for Afro-Caribbeans and 6.8% for Asians), secondly to fetal CRL (4.6% for CRL of 45-54 mm, 3.9% for CRL of 55-64 mm, 1.5% for CRL of 65-74 mm and 1.0% for CRL of 75-84 mm) and thirdly, to NT thickness, (1.8% for NT < 2.5 mm, 3.4% for NT 2.5-3.4 mm, 5.0% for NT 3.5-4.4 mm and 11.8% for NT > or = 4.5 mm. In the chromosomally abnormal group the nasal bone was absent in 161/242 (66.9%) with trisomy 21, in 48/84 (57.1%) with trisomy 18, in 7/22 (31.8%) with trisomy 13, in 3/34 (8.8%) with Turner syndrome and in 4/48 (8.3%) with other defects.



At the 11-14-week scan the incidence of absent nasal bone is related to the presence or absence of chromosomal defects, CRL, NT thickness and ethnic origin.
Injury incidence and distribution in elite football--a prospective study of the Danish and the Swedish top divisions.

The Danish and Swedish male top football divisions were studied prospectively from January to June 2001. Exposure to football and injury incidence, severity and distribution were compared between the countries. Swedish players had greater exposure to training (171 vs. 123 h per season, P<0.001), whereas exposure to matches did not differ between the countries. There was a higher risk for injury during training in Denmark than in Sweden (11.8 vs. 6.0 per 1000 h, P<0.01), whereas for match play there was no difference (28.2 vs. 26.2 per 1000 h). The risk for incurring a major injury (absence from football more than 4 weeks) was greater in Denmark (1.8 vs. 0.7 per 1000 h, P = 0.002). The distribution of injuries according to type and location was similar in both countries. Of all injuries in Denmark and Sweden, overuse injury accounted for 39% and 38% (NS), and re-injury for 30% and 24% (P = 0.032), respectively. The greater training exposure and the long pre-season period in Sweden may explain some of the reported differences.
Anxiety, Stress, and Trauma Symptoms in African Americans: Negative Affectivity Does Not Explain the Relationship between Microaggressions and Psychopathology.

Prior research has demonstrated a clear relationship between experiences of racial microaggressions and various indicators of psychological unwellness. One concern with these findings is that the role of negative affectivity, considered a marker of neuroticism, has not been considered. Negative affectivity has previously been correlated to experiences of racial discrimination and psychological unwellness and has been suggested as a cause of the observed relationship between microaggressions and psychopathology. We examined the relationships between self-reported frequency of experiences of microaggressions and several mental health outcomes (i.e., anxiety [Beck Anxiety Inventory], stress [General Ethnic and Discrimination Scale], and trauma symptoms [Trauma Symptoms of Discrimination Scale]) in 177 African American and European American college students, controlling for negative affectivity (the Positive and Negative Affect Schedule) and gender. Results indicated that African Americans experience more racial discrimination than European Americans. Negative affectivity in African Americans appears to be significantly related to some but not all perceptions of the experience of discrimination. A strong relationship between racial mistreatment and symptoms of psychopathology was evident, even after controlling for negative affectivity. In summary, African Americans experience clinically measurable anxiety, stress, and trauma symptoms as a result of racial mistreatment, which cannot be wholly explained by individual differences in negative affectivity. Future work should examine additional factors in these relationships, and targeted interventions should be developed to help those suffering as a result of racial mistreatment and to reduce microaggressions.
A Critical Analysis on the Security Concerns of Internet of Things (IoT)

Internet of Things (IoT) has been a major research topic for almost a decade now, where physical objects would be interconnected as a result of convergence of various existing technologies. IoT is rapidly developing; however there are uncertainties about its security and privacy which could affect its sustainable development. This paper analyzes the security issues and challenges and provides a well defined security architecture as a confidentiality of the user&apos;s privacy and security which could result in its wider adoption by masses.
Smooth Ramps: Walking the Straight and Narrow Path through Color Space

Smoothly shaded color ramps, important for presentation graphics and computer imaging, are difficult for color managed systems utilizing device profiles. The causes for disruptive artifacts such as contours and banding are examined and a set of visual limits are established that, if met will avoid them. Based on these visual thresholds, an analysis of the numeric representation and processing of color data in an ICC profile-based environment yields some requirements for device profiles and their use. Specifically, we find that 8-bit precision and inadequate table indexing resolution cause contour artifacts. Banding is caused indirectly from the inversion of noisy and nonlinear printer color data when the profile was created. The noise is not instrument noise, but rather due to the inconsistency of printer output. Some proposals for improving this stage of profile making are suggested. Examples are provided to illustrate the sources of difficulties in rendering smooth and uniform color ramps.
Reinforcement Learning Based Conversational Search Assistant

In this work, we develop an end-to-end Reinforcement Learning based architecture for a conversational search agent to assist users in searching on an e-commerce marketplace for digital assets. Our approach caters to a search task fundamentally different from the ones which have limited search modalities where the user can express his preferences objectively. The system interacts with the users to display search results to the queries, and gauges user’s intent and context of the conversation to choose the next action and reply. To train the agent in the absence of true conversation data, a virtual user is constructed to model a human user using the query and session logs from a major stock photography and digital assets marketplace. The system provides an alternative that is more engaging than the traditional search while maintaining similar effectiveness. This work provides a mechanism to build and deploy bootstrapped version of an effective conversational agent from readily available query log data. The system can then be used to acquire true conversational data and be fine-tuned further. The methodology discussed in this paper can be extended to e-commerce domains in general.
Muscle dysmorphia: Could it be classified as an addiction to body
image?

Muscle dysmorphia (MD) describes a condition characterised by a misconstrued body image in which individuals who interpret their body size as both small or weak even though they may look normal or highly muscular.MD has been conceptualized as a type of body dysmorphic disorder, an eating disorder, and obsessive–compulsive disorder symptomatology.  Through a review of the most salient literature on MD, this paper proposes an alternative classification of MD--the ‘Addiction to Body Image’ (ABI) model--using Griffiths (2005)addiction components model as the framework in which to define MD as an addiction.



It is argued the addictive activity in MD is the maintaining of body image via a number of different activities such as bodybuilding, exercise,eating certain foods, taking specific drugs (e.g., anabolic steroids), shopping for certain foods, food supplements,and the use or purchase of physical exercise accessories). In the ABI model, the perception of the positive effects on the self-body image is accounted for as a critical aspect of the MD condition (rather than addiction to exercise or certain types of eating disorder).



Based on empirical evidence to date, it is proposed that MD could be re-classified as an addiction due to the individual continuing to engage in maintenance behaviours that may cause long-term harm.
Models for open innovation in the pharmaceutical industry.

The nature of the pharmaceutical industry is such that the main driver for its growth is innovation. In view of the vast challenges that the industry has been facing for several years and, in particular, how to manage stagnating research and development (R&D) productivity, pharmaceutical companies have opened their R&D organizations to external innovation. Here, we identify and characterize four new types of open innovator, which we call 'knowledge creator', 'knowledge integrator', 'knowledge translator' and 'knowledge leverager', and which describe current open R&D models.
An Exploratory Study of Vicarious Trauma Among Therapist Trainees

The current study explored vicarious trauma among therapist trainees in relation to history of trauma, experience level, trauma-specific training, and defense style. Students in graduate clinical and counseling psychology training programs (N 129) completed the Trauma Symptom Inventory, Defense Style Questionnaire, and an experience questionnaire. Results indicated trauma symptoms were significantly associated with defense style, which appeared to moderate personal trauma history and experience level. Trauma-specific training was also independently related to trauma symptoms. Notably, over half the sample reported a self-sacrificing defense style, which was a risk factor for vicarious trauma. Training implications of the findings are discussed.
Systemic effect of crude extract from rhizome of Drynaria fortunei on bone formation in mice.

The structure of the bones of mice with and without consumption of Gusuibu extracts were compared. Twenty 8-week-old male BALB/c mice were divided into two groups. In the control group ten mice were daily fed a normal diet and distilled water for drinking. In the Gusuibu group ten mice were daily fed a normal diet and distilled water mixed with Gusuibu extract for drinking. The mice were kept for 5 weeks and were then killed. Using micro-computed tomography, 20 micro-tomographic slices with an increment of 0.25 mm were acquired to cover the proximal end of the left tibia of each mouse. Quantitative morphometry of the bone structure was performed. The results showed that consumption of Gusuibu extract increased the bone volume/tissue volume ratio by 6.45%. The bone trabeculae were increased by 10.00% in number so that the bone density was increased. To conclude, Gusuibu extract taken orally increased bone density.
Human posture recognition using active contours and radial basis function neural network

In this paper an automated video surveillance system for human posture recognition using active contours and neural networks is presented. Localization of moving objects in the scene and human posture estimation are key features of the proposed architecture. The system architecture consists of five sequential modules that include the moving target detection process, two levels of segmentation process for interested element localization, features extraction of the object shape and a human posture classification system based on the radial basis functions neural network. Moving objects are detected by using an adaptive background subtraction method with an automatic background adaptation speed parameter and a new fast gradient vector flow snake algorithm for the elements segmentation is proposed. The developed system has been tested for the classification of three different postures such as standing, bending and squatting considering different kinds of feature. Results are promising and the architecture is also useful for the discrimination of human activities.
A DAPTIVE PREDICTION TIME FOR SEQUENCE CLASSIFICATION

In this paper, we propose a recurrent neural network architecture for early sequence classification, when the model is required to output a label as soon as possible with negligible decline in accuracy. Our model is capable of learning how many sequence tokens it needs to observe in order to make a prediction; moreover, the number of steps required differs for each sequence. Experiments on sequential MNIST show that the proposed architecture focuses on different sequence parts during inference, which correspond to contours of the handwritten digits. We also demonstrate the improvement in the prediction quality with a simultaneous reduction in the prefix size used, the extent of which depends on the distribution of distinct class features over time.
LEAP for DEAF : A Sign Language To Speech Translator

Sign language is vital for facilitating communication between hearing impaired and the rest of society. Researchers in Sign language recognition had tailored completely different sensors to capture hand signs. Gloves, digital cameras, depth cameras and Kinect were used instead in most systems. Owing to signs closeness ,input accuracy is a terribly essential constraint to achieve a high recognition accuracy. Our aim is to design a Sign Language to Speech Translation system for ISL(i.e. Indian Sign Language) based on a brand new digital 3D motion detector referred to as Leap Motion, that consists of two inbuilt cameras and three infrared sensors that capture 3-D dynamic hand gestures. The palm-sized Leap Motion sensor provides far more portable and economical solution than Cyber glove or Microsoft Kinect employed in existing studies . This sensor tackles the major issues in vision-based systems like skin color, lighting etc... The planned system will make use of DTW algorithm as a classifier for converting hand gestures into an appropriate text as well as an audible speech.
Design and control of antagonistic robot joint with Twisted String Actuators

In this paper, antagonistic robot joint which uses the Twisted String Actuator is developed. One axis robot joint is antagonistically driven by two Twisted String Actuators. This paper introduces the robot joint design and the performance of one axis robot. The position control is performed for antagonistic robot joint. The non-linearity of wire twist model causes the internal locking problem. The proposed position control algorithm and experiment results are presented.
EEG and ERP biomarkers of Alzheimer's disease: a critical review.

Here we critically review studies that used electroencephalography (EEG) or event-related potential (ERP) indices as a biomarker of Alzheimer's disease. In the first part we overview studies that relied on visual inspection of EEG traces and spectral characteristics of EEG. Second, we survey analysis methods motivated by dynamical systems theory (DST) as well as more recent network connectivity approaches. In the third part we review studies of sleep.  Next, we compare the utility of early and late ERP components in dementia research. In the section on mismatch negativity (MMN) studies we summarize their results and limitations and outline the emerging field of computational neurology. In the following we overview the use of EEG in the differential diagnosis of the most common neurocognitive disorders. Finally, we provide a summary of the state of the field and conclude that several promising EEG/ERP indices of synaptic neurotransmission are worth considering as potential biomarkers. Furthermore, we highlight some practical issues and discuss future challenges as well.
A 25 Gb/s Hybrid-Integrated Silicon Photonic Source-Synchronous Receiver With Microring Wavelength Stabilization

Single-mode wavelength-division multiplexing (WDM) optical links are an attractive technology to meet the growing interconnect bandwidth demand in data center applications. This paper presents a multi-channel hybridintegrated photonic receiver based on microring drop filters and waveguide photodetectors implemented in a 130 nm SOI process and high-speed optical front-ends designed in 65 nm CMOS. The source-synchronous receiver utilizes an LC injection-locked oscillator (ILO) in the clock path for improved jitter filtering, while maintaining correlated jitter tracking with the data channels. Receiver sensitivity is improved with a large input-stage feedback resistor transimpedance amplifier (TIA) cascaded with an adaptively-tuned continuous-time linear equalizer (CTLE). In order to stabilize the microring drop filter resonance wavelength, a peak-detector-based thermal tuning loop is implemented with a 0.7 nm range at 43 μW/GHz efficiency. When tested with a waveguide photodetector with 0.45 A/W responsivity, the receiver achieves -8.0 dBm OMA sensitivity at a BER = 10-12 with a jitter tolerance corner frequency near 20 MHz and a per-channel power consumption of 17 mW including amortized clocking power.
Research on Key Problems of Data Quality in Large Industrial Data Environment

At present, the modern manufacturing and management concepts such as digitalization, networking and intellectualization have been popularized in the industry, and the degree of industrial automation and information has been improved unprecedentedly. Industrial products are everywhere in the world. They are involved in design, manufacture, operation, maintenance and recycling. The whole life cycle involves huge amounts of data. Improving data quality is very important for data mining and data analysis. To solve the problem of data inconsistency is a very important part of improving data quality.
Determining the challenges of organizational social media adoption and use

Organizations often face challenges with the adoption and use of new information systems, and social media is no exception. In this exploratory case study, we aim to identify internal and external challenges related to the adoption and use of social media in a large case company. Our findings show that internal challenges include resources, ownership, authorization, attitudes and economic issues, whereas external challenges are associated with company reputation, legal issues and public/private network identity. We add to the knowledge created by previous studies by introducing the challenges related to ownership and authorization of social media services, which were found to be of high relevance in corporate social media adoption. In order to overcome these obstacles, we propose that organizations prepare strategies and guidelines for social media adoption and use.
How Does Internal Control Regulation Affect Financial Reporting ?

Internal control regulation effectiveness remains controversial given the recent financial crisis. To address this issue we examine the financial reporting effects of the Federal Depository Insurance Corporation Improvement Act (FDICIA) internal control provisions. Exemptions from these provisions for banks with assets under $500 million and for non-US banks provides two unaffected control samples. Our difference-indifferences method suggests that FDICIA-mandated internal control requirements increased loan-loss provision validity, earnings persistence and cash-flow predictability and reduced benchmark-beating and accounting conservatism for affected versus unaffected banks. More pronounced effects in interim versus fourth quarters suggest that greater auditor presence substitutes for internal control regulation.