nils-herrmann/clean_scirepeval huggingface dataset:
A 'snip' in time: what is the best age to circumcise?

Circumcision is a common procedure, but regional and societal attitudes differ on whether there is a need for a male to be circumcised and, if so, at what age. This is an important issue for many parents, but also pediatricians, other doctors, policy makers, public health authorities, medical bodies, and males themselves.



We show here that infancy is an optimal time for clinical circumcision because an infant's low mobility facilitates the use of local anesthesia, sutures are not required, healing is quick, cosmetic outcome is usually excellent, costs are minimal, and complications are uncommon. The benefits of infant circumcision include prevention of urinary tract infections (a cause of renal scarring), reduction in risk of inflammatory foreskin conditions such as balanoposthitis, foreskin injuries, phimosis and paraphimosis. When the boy later becomes sexually active he has substantial protection against risk of HIV and other viral sexually transmitted infections such as genital herpes and oncogenic human papillomavirus, as well as penile cancer. The risk of cervical cancer in his female partner(s) is also reduced. Circumcision in adolescence or adulthood may evoke a fear of pain, penile damage or reduced sexual pleasure, even though unfounded. Time off work or school will be needed, cost is much greater, as are risks of complications, healing is slower, and stitches or tissue glue must be used.



Infant circumcision is safe, simple, convenient and cost-effective. The available evidence strongly supports infancy as the optimal time for circumcision.
Estimation and calibration algorithms for distributed sampling systems

Distributed Sampling Systems by Vijay Divi S.B., Massachusetts Institute of Technology (2002) S.B., Massachusetts Institute of Technology (2003) M.Eng., Massachusetts Institute of Technology (2004) Submitted to the Department of Electrical Engineering and Computer Science in partial fulfillment of the requirements for the degree of Doctor of Philosophy in Electrical Engineering and Computer Science at the MASSACHUSETTS INSTITUTE OF TECHNOLOGY September 2008
Convolutional neural networks for chemical-disease relation extraction are improved with character-based word embeddings

We investigate the incorporation of character-based word representations into a standard CNN-based relation extraction model. We experiment with two common neural architectures, CNN and LSTM, to learn word vector representations from character embeddings. Through a task on the BioCreative-V CDR corpus, extracting relationships between chemicals and diseases, we show that models exploiting the character-based word representations improve on models that do not use this information, obtaining state-of-the-art result relative to previous neural approaches.
Implementation of PIC Based Vehicle ’ s Attitude Estimation System Using MEMS Inertial Sensors and Kalman Filter

In this paper, one dimensional drift free attitude estimation system using accelerometer and gyroscope was studied. The proposed system fuses data from accelerometers and gyroscopes by means of a Kalman filter. A PIC microcontroller is used for estimating the angle value in the proposed system. Moreover, this controller does all data acquisition and interfacing tasks. The experimental results are given to verify the proposed microcontroller based estimation system. Keywordsaccelerometer, gyroscope, Kalman filter, microcontroller, sensor data fusion, tilt angle estimation
The Statistical Analysis of Roll Call Data

We develop a Bayesian procedure for estimation and inference for spatial models of roll call voting. This approach is extremely flexible, applicable to any legislative setting, irrespective of size, the extremism of the legislators’ voting histories, or the number of roll calls available for analysis. The model is easily extended to let other sources of information inform the analysis of roll call data, such as the number and nature of the underlying dimensions, the presence of party whipping, the determinants of legislator preferences, and the evolution of the legislative agenda; this is especially helpful since generally it is inappropriate to use estimates of extant methods (usually generated under assumptions of sincere voting) to test models embodying alternate assumptions (e.g., log-rolling, party discipline). A Bayesian approach also provides a coherent framework for estimation and inference with roll call data that eludes extant methods; moreover, via Bayesian simulation methods, it is straightforward to generate uncertainty assessments or hypothesis tests concerning any auxiliary quantity of interest or to formally compare models. In a series of examples we show how our method is easily extended to accommodate theoretically interesting models of legislative behavior. Our goal is to provide a statistical framework for combining the measurement of legislative preferences with tests of models of legislative behavior.
Annotation in outdoor augmented reality

Annotation, the process of adding extra virtual information to an object, is one of the most common uses for augmented reality. Although annotation is widely used in augmented reality, there is no general agreed-upon definition of what precisely constitutes an annotation in this context. In this paper, we propose a taxonomy of annotation, describing what constitutes an annotation and outlining different dimensions along which annotation can vary. Using this taxonomy we also highlight what styles of annotation are used in different types of applications and areas where further work needs to be done to
Wideband High-Gain Open Resonator Antenna Using a Spherically Modified, Second-Order Cavity

In this communication, we present a simple yet unconventional wideband resonant cavity antenna (RCA) with high gain and large gain-bandwidth product (GBP). The bandwidth enhancement of the RCA is approached by using a second-order height resonant cavity comprising a dielectric slab of high permittivity as the partially reflective surface and a ground plane with spherically modified geometry. It is shown that by imitating an open resonator structure, the spherically modified cavity can support multiple quasi-Laguerre–Gaussian beam modes and hence, dramatically improve the operation bandwidth of the RCA. A RCA with large GBP is designed, simulated, and then verified through measurement. Measured results show a bandwidth of 25% with a peak gain of 17.7 dBi. The proposed low-cost and easy-fabricate method shows its effectiveness in increasing the bandwidth for the RCA.
Explainable and Explicit Visual Reasoning over Scene Graphs

We aim to dismantle the prevalent black-box neural architectures used in complex visual reasoning tasks, into the proposed eXplainable and eXplicit Neural Modules (XNMs), which advance beyond existing neural module networks towards using scene graphs — objects as nodes and the pairwise relationships as edges — for explainable and explicit reasoning with structured knowledge. XNMs allow us to pay more attention to teach machines how to “think”, regardless of what they “look”. As we will show in the paper, by using scene graphs as an inductive bias, 1) we can design XNMs in a concise and flexible fashion, i.e., XNMs merely consist of 4 meta-types, which significantly reduce the number of parameters by 10 to 100 times, and 2) we can explicitly trace the reasoning-flow in terms of graph attentions. XNMs are so generic that they support a wide range of scene graph implementations with various qualities. For example, when the graphs are detected perfectly, XNMs achieve 100% accuracy on both CLEVR and CLEVR CoGenT, establishing an empirical performance upper-bound for visual reasoning; when the graphs are noisily detected from real-world images, XNMs are still robust to achieve a competitive 67.5% accuracy on VQAv2.0, surpassing the popular bag-of-objects attention models without graph structures.
A learning style classification mechanism for e-learning

With the growing demand in e-learning, numerous research works have been done to enhance teaching quality in e-learning environments. Among these studies, researchers have indicated that adaptive learning is a critical requirement for promoting the learning performance of students. Adaptive learning provides adaptive learning materials, learning strategies and/or courses according to a student’s learning style. Hence, the first step for achieving adaptive learning environments is to identify students’ learning styles. This paper proposes a learning style classification mechanism to classify and then identify students’ learning styles. The proposed mechanism improves k-nearest neighbor (k-NN) classification and combines it with genetic algorithms (GA). To demonstrate the viability of the proposed mechanism, the proposed mechanism is implemented on an open-learning management system. The learning behavioral features of 117 elementary school students are collected and then classified by the proposed mechanism. The experimental results indicate that the proposed classification mechanism can effectively classify and identify students’ learning styles.
A Mathematical Theory of Communication

This paper opened the new area the information theory. Before this paper, most people believed that the only way to make the error probability of transmission as small as desired is to reduce the data rate (such as a long repetition scheme). However, surprisingly this paper revealed that it does not need to reduce the data rate for achieving that much of small errors. It proved that we can get some positive data rate that has the same small error probability and also there is an upper bound of the data rate, which means we cannot achieve the data rate with any encoding scheme that has small enough error probability over the upper bound.
MelanoGANs: High Resolution Skin Lesion Synthesis with GANs

Generative Adversarial Networks (GANs) have been successfully used to synthesize realistically looking images of faces, scenery and even medical images. Unfortunately, they usually require large training datasets, which are often scarce in the medical field, and to the best of our knowledge GANs have been only applied for medical image synthesis at fairly low resolution. However, many state-of-theart machine learning models operate on high resolution data as such data carries indispensable, valuable information. In this work, we try to generate realistically looking high resolution images of skin lesions with GANs, using only a small training dataset of 2000 samples. The nature of the data allows us to do a direct comparison between the image statistics of the generated samples and the real dataset. We both quantitatively and qualitatively compare state-of-the-art GAN architectures such as DCGAN and LAPGAN against a modification of the latter for the task of image generation at a resolution of 256x256px. Our investigation shows that we can approximate the real data distribution with all of the models, but we notice major differences when visually rating sample realism, diversity and artifacts. In a set of use-case experiments on skin lesion classification, we further show that we can successfully tackle the problem of heavy class imbalance with the help of synthesized high resolution melanoma samples.
Reflective Informatics Through Family Storytelling: Self-discovering Physical Activity Predictors

HCI research has increasingly examined how sensing technologies can help people capture and visualize data about their health-related behaviors. Yet, few systems help people reflect more fundamentally on the factors that influence behaviors such as physical activity (PA). To address this research gap, we take a novel approach, examining how such reflections can be stimulated through a medium that generations of families have used for reflection and teaching: storytelling. Through observations and interviews, we studied how 13 families interacted with a low-fidelity prototype, and their attitudes towards this tool. Our prototype used storytelling and interactive prompts to scaffold reflection on factors that impact children's PA. We contribute to HCI research by characterizing how families interacted with a story-driven reflection tool, and how such a tool can encourage critical processes for behavior change. Informed by the Transtheoretical Model, we present design implications for reflective informatics systems.
Pornography and teenagers: the importance of individual differences.

This article focuses on the effects of exposure to pornography on teenagers, particularly males, and concentrates on sexually aggressive outcomes and on the characteristics of the individual as crucial in determining whether pornography consumption may or may not lead to sexually aggressive outcomes. In future work, it is important not to use an overly simplistic lens of focus in which pornography exposure is seen as generally harmful or not. Depending on particular constellations of personality characteristics, the effects of pornography may differ considerably among different teenagers as well as within different cultures. The research suggests that particular concerns may be needed for those who are highly frequent consumers of pornography, those who seek out sexually violent content, and those who also have other risk factors.
PR-Set7 and H4K20me1: at the crossroads of genome integrity, cell cycle, chromosome condensation, and transcription.

Histone post-translational modifications impact many aspects of chromatin and nuclear function. Histone H4 Lys 20 methylation (H4K20me) has been implicated in regulating diverse processes ranging from the DNA damage response, mitotic condensation, and DNA replication to gene regulation. PR-Set7/Set8/KMT5a is the sole enzyme that catalyzes monomethylation of H4K20 (H4K20me1). It is required for maintenance of all levels of H4K20me, and, importantly, loss of PR-Set7 is catastrophic for the earliest stages of mouse embryonic development. These findings have placed PR-Set7, H4K20me, and proteins that recognize this modification as central nodes of many important pathways. In this review, we discuss the mechanisms required for regulation of PR-Set7 and H4K20me1 levels and attempt to unravel the many functions attributed to these proteins.
Fertility in male patients with advanced Hodgkin lymphoma treated with BEACOPP: a report of the German Hodgkin Study Group (GHSG).

To date, there is little information on the impact of more aggressive treatment regimen such as BEACOPP (bleomycin, etoposide, doxorubicin, cyclophosphamide, vincristine, procarbazine, and prednisone) on the fertility of male patients with Hodgkin lymphoma (HL). We evaluated the impact of BEACOPP regimen on fertility status in 38 male patients with advanced-stage HL enrolled into trials of the German Hodgkin Study Group (GHSG). Before treatment, 6 (23%) patients had normozoospermia and 20 (77%) patients had dysspermia. After treatment, 34 (89%) patients had azoospermia, 4 (11%) had other dysspermia, and no patients had normozoospermia. There was no difference in azoospermia rate between patients treated with BEACOPP baseline and those given BEACOPP escalated (93% vs 87%, respectively; P > .999). After treatment, most of patients (93%) had abnormal values of follicle-stimulating hormone, whereas the number of patients with abnormal levels of testosterone and luteinizing hormone was less pronounced-57% and 21%, respectively. In univariate analysis, none of the evaluated risk factors (ie, age, clinical stage, elevated erythrocyte sedimentation rate, B symptoms, large mediastinal mass, extranodal disease, and 3 or more lymph nodes) was statistically significant. Male patients with HL are at high risk of infertility after treatment with BEACOPP.
LEAD TIME REDUCTION VIA PREPOSITIONING OF INVENTORY IN AN INDUSTRIAL CONSTRUCTION SUPPLY CHAIN

Lead time reduction is a key concern of many industrial buyers of capital facilities given current economic conditions. Supply chain initiatives in manufacturing settings have led owners to expect that dramatic reductions in lead time are possible in all phases of their business, including the delivery of capital materials. Further, narrowing product delivery windows and increasing pressure to be first-tomarket create significant external pressure to reduce lead time. In this paper, a case study is presented in which an owner entered the construction supply chain to procure and position key long-lead materials. The materials were held at a position in the supply chain selected to allow some flexibility for continued customization, but dramatic reduction in the time-to-site. Simulation was used as a tool to consider time-to-site tradeoffs for multiple inventory locations so as to better match the needs of the construction effort.
Effective communication skills in nursing practice.

This article highlights the importance of effective communication skills for nurses. It focuses on core communication skills, their definitions and the positive outcomes that result when applied to practice. Effective communication is central to the provision of compassionate, high-quality nursing care. The article aims to refresh and develop existing knowledge and understanding of effective communication skills. Nurses reading this article will be encouraged to develop a more conscious style of communicating with patients and carers, with the aim of improving health outcomes and patient satisfaction.
Secure Smart Homes: Opportunities and Challenges

The Smart Home concept integrates smart applications in the daily human life. In recent years, Smart Homes have increased security and management challenges due to the low capacity of small sensors, multiple connectivity to the Internet for efficient applications (use of big data and cloud computing), and heterogeneity of home systems, which require inexpert users to configure devices and micro-systems. This article presents current security and management approaches in Smart Homes and shows the good practices imposed on the market for developing secure systems in houses. At last, we propose future solutions for efficiently and securely managing the Smart Homes.
The hygroscopic behavior of plant fibers: a review

Environmental concern has resulted in a renewed interest in bio-based materials. Among them, plant fibers are perceived as an environmentally friendly substitute to glass fibers for the reinforcement of composites, particularly in automotive engineering. Due to their wide availability, low cost, low density, high-specific mechanical properties, and eco-friendly image, they are increasingly being employed as reinforcements in polymer matrix composites. Indeed, their complex microstructure as a composite material makes plant fiber a really interesting and challenging subject to study. Research subjects about such fibers are abundant because there are always some issues to prevent their use at large scale (poor adhesion, variability, low thermal resistance, hydrophilic behavior). The choice of natural fibers rather than glass fibers as filler yields a change of the final properties of the composite. One of the most relevant differences between the two kinds of fiber is their response to humidity. Actually, glass fibers are considered as hydrophobic whereas plant fibers have a pronounced hydrophilic behavior. Composite materials are often submitted to variable climatic conditions during their lifetime, including unsteady hygroscopic conditions. However, in humid conditions, strong hydrophilic behavior of such reinforcing fibers leads to high level of moisture absorption in wet environments. This results in the structural modification of the fibers and an evolution of their mechanical properties together with the composites in which they are fitted in. Thereby, the understanding of these moisture absorption mechanisms as well as the influence of water on the final properties of these fibers and their composites is of great interest to get a better control of such new biomaterials. This is the topic of this review paper.
Developments on Balanced Scorecard : A Historical Review

Balanced Scorecard is considered as the world widely used Performance Management System by organizations. Around 57% organizations of the world are using the Balanced Scorecard tool for improving their Organizational Performance . This technique of performance evaluation and management was coined by the Kaplan and Norton in 1992. From that date to 2012 a lot of work has been done by the academicians and practitioner on the Balanced Scorecard. This study is summarizing the major studies conducted on Balanced Scorecard from 1992 to 2012. Summing up all the criticism and appreciations on Balanced Scorecard, the study is suggesting some guidelines for improving the Balanced Scorecard in the light of previous researches conducted on Balanced
The Articulated Alar Rim Graft: Reengineering the Conventional Alar Rim Graft for Improved Contour and Support.

Surgical refinement of the wide nasal tip is challenging. Achieving an attractive, slender, and functional tip complex without destabilizing the lower nasal sidewall or deforming the contracture-prone alar rim is a formidable task. Excisional refinement techniques that rely upon incremental weakening of wide lower lateral cartilages (LLC) often destabilize the tip complex and distort tip contour. Initial destabilization of the LLC is usually further exacerbated by "shrink-wrap" contracture, which often leads to progressive cephalic retraction of the alar margin. The result is a misshapen tip complex accentuated by a conspicuous and highly objectionable nostril deformity that is often very difficult to treat. The "articulated" alar rim graft (AARG) is a modification of the conventional rim graft that improves treatment of secondary alar rim deformities, including postsurgical alar retraction (PSAR). Unlike the conventional alar rim graft, the AARG is sutured to the underlying tip complex to provide direct stationary support to the alar margin, thereby enhancing graft efficacy. When used in conjunction with a well-designed septal extension graft (SEG) to stabilize the central tip complex, lateral crural tensioning (LCT) to tighten the lower nasal sidewalls and minimize soft-tissue laxity, and lysis of scar adhesions to unfurl the retracted and scarred nasal lining, the AARG can eliminate PSAR in a majority of patients. The AARG is also highly effective for prophylaxis against alar retraction and in the treatment of most other contour abnormalities involving the alar margin. Moreover, the AARG requires comparatively little graft material, and complications are rare. We present a retrospective series of 47 consecutive patients treated with the triad of AARG, SEG, and LCT for prophylaxis and/or treatment of alar rim deformities. Outcomes were favorable in nearly all patients, and no complications were observed. We conclude the AARG is a simple and effective method for avoiding and correcting most alar rim deformities.
Evolutionary programming based recommendation system for online shopping

In this paper, we propose an interactive evolutionary programming based recommendation system for online shopping that estimates the human preference based on eye movement analysis. Given a set of images of different clothes, the eye movement patterns of the human subjects while looking at the clothes they like differ from clothes they do not like. Therefore, in the proposed system, human preference is measured from the way the human subjects look at the images of different clothes. In other words, the human preference can be measured by using the fixation count and the fixation length using an eye tracking system. Based on the level of human preference, the evolutionary programming suggests new clothes that close the human preference by operations such as selection and mutation. The proposed recommendation is tested with several human subjects and the experimental results are demonstrated.