nils-herrmann/clean_scirepeval huggingface dataset:
Does #like4like indeed provoke more likes?

Hashtags, created by social network users, have gained a huge popularity in recent years. As a kind of metatag for organizing information, hashtags in online social networks, especially in Instagram, have greatly facilitated users' interactions. In recent years, academia starts to use hashtags to reshape our understandings on how users interact with each other.  In this paper, we study whether #like4like indeed serves the purpose it is created for, i.e., will #like4like provoke more likes? We first perform a general analysis of #like4like with 1.8 million photos collected from Instagram, and discover that its quantity has dramatically increased by 1,300 times from 2012 to 2016. Then, we study whether #like4like will attract likes for photo publishers; results show that it is not #like4like but actually photo contents attract more likes, and the lifespan of a #like4like photo is quite limited. In the end, we study whether users who like #like4like photos will receive likes from #like4like publishers. However, results show that more than 90% of the publishers do not keep their promises, i.e., they will not like back others who like their #like4like photos; and for those who keep their promises, the photos which they like back are often randomly selected.
Urgent penectomy in a patient presenting with epidermoid carcinoma of the penis associated to myiasis.

The objective of this study is to describe the case of a patient presenting advanced epidermoid carcinoma of the penis associated to myiasis. A 41-year-old patient presenting with a necrotic lesion of the distal third of the penis infested with myiasis was attended in the emergency room of our hospital and was submitted to an urgent penectomy. This is the first case of penile cancer associated to myiasis described in the literature. This case reinforces the need for educative campaigns to reduce the incidence of this disease in developing countries.
Probably Approximately Metric-Fair Learning

The seminal work of Dwork et al.  We show that this can lead to computational intractability even for simple fair-learning tasks. With this motivation in mind, we introduce and study a relaxed notion of approximate metric-fairness: for a random pair of individuals sampled from the population, with all but a small probability of error, if they are similar then they should be treated similarly. We formalize the goal of achieving approximate metric-fairness simultaneously with best-possible accuracy as Probably Approximately Correct and Fair (PACF) Learning. We show that approximate metricfairness does generalize, and leverage these generalization guarantees to construct polynomialtime PACF learning algorithms for the classes of linear and logistic predictors.  Research supported by the ISRAEL SCIENCE FOUNDATION (grant No. 5219/17). gal.yona@gmail.com. Research supported by the ISRAEL SCIENCE FOUNDATION (grant No. 5219/17).
Promoting Recommendations: An Attack on Collaborative Filtering

The growth and popularity of Internet applications has reinforced the need for effective information filtering techniques. The collaborative filtering approach is now a popular choice and has been implemented in many on-line systems. While many researchers have proposed and compared the performance of various collaborative filtering algorithms, one important performance measure has been omitted from the research to date that is the robustness of the algorithm. In essence, robustness measures the power of the algorithm to make good predictions in the presence of noisy data. In this paper, we argue that robustness is an important system characteristic, and that it must be considered from the point-of-view of potential attacks that could be made on a system by malicious users. We propose a definition for system robustness, and identify system characteristics that influence robustness. Several attack strategies are described in detail, and experimental results are presented for the scenarios outlined.
Amino Acid-based Formula in Cow's Milk Allergy: Long-term Effects on Body Growth and Protein Metabolism.

The long-term effects of amino acid-based formula (AAF) in the treatment of cow's milk allergy (CMA) are largely unexplored. The present study comparatively evaluates body growth and protein metabolism in CMA children treated with AAF or with extensively hydrolyzed whey formula (eHWF), and healthy controls.



A 12-month multicenter randomized control trial was conducted in outpatients with CMA (age 5-12 m) randomized in 2 groups, treated with AAF (group 1) and eHWF (group 2), and compared with healthy controls (group 3) fed with follow-on (if age <12 months) or growing-up formula (if age >12 months). At enrolment (T0), after 3 (T3), 6 (T6), and 12 months (T12) a clinical evaluation was performed. At T0 and T3, in subjects with CMA serum levels of albumin, urea, total protein, retinol-binding protein, and insulin-like growth factor 1 were measured.



Twenty-one subjects in group 1 (61.9% boys, age 6.5 ± 1.5 months), 19 in group 2 (57.9% boys, age 7 ± 1.7 months) and 25 subjects in group 3 (48% boys, age 5.5 ± 0.5 months) completed the study. At T0, the weight z score was similar in group 1 (-0.74) and 2 (-0.76), with differences compared to group 3 (-0.17, P < 0.05). At T12, the weight z score value was similar between the 3 groups without significant differences. There were no significant changes in protein metabolism in children in groups 1 and 2.



Long-term treatment with AAF is safe and allows adequate body growth in children with CMA.
Modeling of losses in substrate integrated waveguide by Boundary Integral-Resonant Mode Expansion method

This paper presents an efficient technique for the evaluation of different types of losses in substrate integrated waveguide (SIW). This technique is based on the Boundary Integral-Resonant Mode Expansion (BI-RME) method in conjunction with a perturbation approach. This method also permits to derive automatically multimodal and parametric equivalent circuit models of SIW discontinuities, which can be adopted for an efficient design of complex SIW circuits. Moreover, a comparison of losses in different types of planar interconnects (SIW, microstrip, coplanar waveguide) is presented.
Chinese and Other Asian Modernisms : A Comparative View of Art-Historical Contexts in the Twentieth Century

Using a comparative analysis approach, this article examines the development, characteristics and issues concerning the discourse of modern Asian art in the twentieth century, with the aim of bringing into picture the place of Asia in the history of modernism. The wide recognition of the Western modernist canon as centre and universal displaces the contribution and significance of the non-Western world in the modern movement. From a cross-cultural perspective, this article demonstrates that modernism in the field of visual arts in Asia, while has had been complex and problematic, nevertheless emerged. Rather than treating Asian art as a generalized subject, this article argues that, with their subtly different notions of culture, identity and nationhood, the modernisms that emerged from various nations in this region are diverse and culturally specific. Through the comparison of various art-historical contexts in this region (namely China, India, Japan and Korea), this article attempts to map out some similarities as well as differences in their pursuit of an autonomous modernist representation.
Chapter 5 – Imaging of the foot and ankle in rheumatoid arthritis

Rheumatoid arthritis (RA) is a chronic progressive systemic inflammatory disease of synovial tissue. Its aetiology is poorly understood, although autoimmune and biomechanical factors are implicated. The overall incidence in the general population is in the region of 1% (Symmons et al. 2002, Lawrence et al. 1998). Females are affected approximately three times more commonly than males (Symmons et al. 2002). Approximately 90% of patients have involvement of the foot or ankle at some point during their disease and 20% of patients present with foot problems (Resnick 2002). Symptoms of the foot usually precede the hands and are affected more severely. Therefore, not only are the feet frequently affected by RA, but also the symptoms often predate other areas. Plain film radiography is the mainstay of imaging of the ankle and foot. In recent years the use of other imaging modalities such as ultrasound (U/S) and magnetic resonance imaging (MRI) have become more important and provide an improved abnormality detection rate due to their ability to image in multiple planes rather than the 2D representation seen with plain film (McGonagle et al. 2001). They are important in not only the diagnosis, but also the follow-up and evaluation of RA (Ostergaard and Szkudlarek 2003). Imaging also plays a pivotal role in diagnosis confirmation in patients with confusing presentations or negative serology. Because bone and cartilage destruction is largely irreversible, a definite radiological diagnosis can drastically alter the patient’s prognosis. The goal of the rheumatologist is to arrest the disease before this stage. Imaging of the foot and ankle in rheumatoid arthritis
Delay bounded spray and wait in delay tolerant networks

Recently, application-specific requirement becomes one of main research challenges in the area of routing for delay tolerant networks. Among various requirements, in this paper, we focus on achieving the desired delivery ratio within bounded given deadline. For this goal, we use analytical model and develop a new forwarding scheme in respective phase. The proposed protocol dynamically adjusts the number of message copies by analytical model and the next hop node is determined depending on the delivery probability and the inter-meeting time of the encountering nodes as well as remaining time. Simulation results demonstrate that our proposed algorithm meets bounded delay with lower overhead than existing protocols in an adaptive way to varying network conditions.
Labelling Topics in Weibo Using Word Embedding and Graph-Based Method

Nowadays, in China, Weibo is becoming an increasingly popular way for people to know what is happening in the world. Labelling topics is of much importance for better understanding the semantics of topics. Existing works mainly focus on deriving candidate labels by exploring the use of external knowledge, which may be more appropriate for well formatted and static documents. Recently, it has been a new trend to generate labels for sparse and dynamic microblogging environment using summarization method. The challenges of labelling topics are how to obtain coherent candidate labels and how to rank the labels. In this paper, based on the latest research work in deep learning, we propose a novel and unified model for labelling topics in Weibo, which firstly adopts word embedding and clustering method to learn dense semantic representation of topic words and mine the coherent candidate topic labels, then, generates interpretable labels using a graph-based model. Experimental results show that topics labels discovered by our model not only have high topic coherence, but also are meaningful and interpretable.
Fatal Ingestion of Chlumsky Disinfectant Solution.

A 32-year-old pregnant woman in the 25th week of pregnancy underwent oral glucose tolerance screening at the diabetologist's. Later that day, she was found dead in her apartment possibly poisoned with Chlumsky disinfectant solution (solutio phenoli camphorata). An autopsy revealed chemical burns in the digestive system. The lungs and the brain showed signs of severe edema. The blood of the woman and fetus was analyzed using gas chromatography with mass spectrometry and revealed phenol, its metabolites (phenyl glucuronide and phenyl sulfate) and camphor. No ethanol was found in the blood samples. Both phenol and camphor are contained in Chlumsky disinfectant solution, which is used for disinfecting surgical equipment in healthcare facilities. Further investigation revealed that the deceased woman had been accidentally administered a disinfectant instead of a glucose solution by the nurse, which resulted in acute intoxication followed by the death of the pregnant woman and the fetus.
Sample-Efficient Deep RL with Generative Adversarial Tree Search

We propose Generative Adversarial Tree Search (GATS), a sample-efficient Deep Reinforcement Learning (DRL) algorithm. While Monte Carlo Tree Search (MCTS) is known to be effective for search and planning in RL, it is often sampleinefficient and therefore expensive to apply in practice. In this work, we develop a Generative Adversarial Network (GAN) architecture to model an environment’s dynamics and a predictor model for the reward function. We exploit collected data from interaction with the environment to learn these models, which we then use for model-based planning. During planning, we deploy a finite depth MCTS, using the learned model for tree search and a learned Q-value for the leaves, to find the best action. We theoretically show that GATS improves the bias-variance tradeoff in value-based DRL. Moreover, we show that the generative model learns the model dynamics using orders of magnitude fewer samples than the Q-learner. In non-stationary settings where the environment model changes, we find the generative model adapts significantly faster than the Q-learner to the new environment.
Treatment intensity and childhood apraxia of speech.

Intensive treatment has been repeatedly recommended for the treatment of speech deficits in childhood apraxia of speech (CAS). However, differences in treatment outcomes as a function of treatment intensity have not been systematically studied in this population.



To investigate the effects of treatment intensity on outcome measures related to articulation, functional communication and speech intelligibility for children with CAS undergoing individual motor speech intervention.


 PROCEDURES
A total of 37 children (32-54 months of age) with CAS received 1×/week (lower intensity) or 2×/week (higher intensity) individual motor speech treatment for 10 weeks. Assessments were carried out before and after a 10-week treatment block to study the effects of variations in treatment intensity on the outcome measures.



The results indicated that only higher intensity treatment (2×/week) led to significantly better outcomes for articulation and functional communication compared with 1×/week (lower intensity) intervention. Further, neither lower nor higher intensity treatment yielded a significant change for speech intelligibility at the word or sentence level. In general, effect sizes for the higher intensity treatment groups were larger for most variables compared with the lower intensity treatment group.



Overall, the results of the current study may allow for modification of service delivery and facilitate the development of an evidence-based care pathway for children with CAS.
Mandibular bone necrosis after use of paraformaldehyde-containing paste

Paraformaldehyde has been used in the past as a pulpotomy agent. However, it has a severe cytotoxic effect and may cause alveolar bone necrosis. Depulpin, a devitalizing agent containing 49% paraformaldehyde, is no longer used frequently due to its severe side effects. In the two cases described in the present study, Depulpin was used as a devitalizing agent during root canal treatment. It caused a gradual loss of sensibility in adjacent teeth, gingival necrosis, and osteomyelitis. This case report demonstrates the serious side effects of using a paraformaldehyde-containing paste as a devitalizing agent for pulp, particularly mandibular bone necrosis.
Using Broad-Context Discriminative Language Modeling on the LAMBADA Word Prediction Task

Since Hinton and Salakhutdinov published their landmark science paper in 2006 ending the previous neural-network winter, research in neural networks has increased dramatically. Researchers have applied neural networks seemingly successfully to various topics in the field of computer science. However, there is a risk that we overlook other methods. Therefore, we take a recent end-to-end neural-network-based work (Dhingra et al., 2018) as a starting point and contrast this work with more classical techniques. This prior work focuses on the LAMBADA word prediction task, where broad context is used to predict the last word of a sentence. It is often assumed that neural networks are good at such tasks where feature extraction is important. We show that with simpler syntactic and semantic features (e.g. Across Sentence Boundary (ASB) N-grams) a state-ofthe-art neural network can be outperformed. Our discriminative language-model-based approach improves the word prediction accuracy from 55.6% to 58.9% on the LAMBADA task. As a next step, we plan to extend this work to other language modeling tasks.
Coded-Seeking: A Simple HDD Speed-Up Concept

Consider a single hard disk drive (HDD) composed of rotating platters and a single magnetic head. We propose a simple internal coding framework for HDDs that uses coding across drive blocks to reduce average block seek times. In particular, instead of the HDD controller seeking individual blocks, the drive performs coded-seeking: It seeks the closest subset of coded blocks, where a coded block contains partial information from multiple uncoded blocks. Coded-seeking is a tool that relaxes the scheduling of a full traveling salesman problem (TSP) on an HDD into a k-TSP. This may provide opportunities for new scheduling algorithms and to reduce average read times.
An unfermented gel component of psyllium seed husk promotes laxation as a lubricant in humans.

In addition to increasing stool weight, supplements of psyllium seed husk produce stools that are slick and gelatinous.



Our purpose was to test the hypothesis that a gel-forming fraction of psyllium escapes microbial fermentation and is responsible for the characteristics that enhance laxation.



Fifteen healthy adults consumed controlled diets for two 7-d periods, one of which included 8.8 g dietary fiber provided by 15 g/d of a psyllium seed husk preparation. All stools were collected and evaluated and diet was monitored throughout.



Psyllium significantly increased the apparent viscosity of an aqueous stool extract, stool moisture, and wet and dry stool weights. A very viscous fraction, not present in low-fiber stool and containing predominantly 2 sugars that are also found in abundance in psyllium husk, was isolated from psyllium stool.



In contrast with other viscous fibers that are fermented completely in the colon, a component of psyllium is not fermented. This gel provided lubrication that facilitated propulsion of colon contents and produced a stool that was bulkier and more moist than were stools resulting with use of comparable amounts of other bowel-regulating fiber sources.
Hiding a Needle in a Haystack: Privacy Preserving Apriori algorithm inMapReduce Framework

In the last few years, Hadoop become a "de facto" standard to process large scale data as an open source distributed system. With combination of data mining techniques, Hadoop improve data analysis utility. That is why, there are amount of research is studied to apply data mining technique to mapreduce framework in Hadoop. However, data mining have a possibility to cause a privacy violation and this threat is a huge obstacle for data mining using Hadoop. To solve this problem, numerous studies have been conducted. However, existing studies were insufficient and had several drawbacks. In this paper, we propose the privacy preserving data mining technique in Hadoop that is solve privacy violation without utility degradation. We focus on association rule mining algorithm that is representative data mining algorithm. We validate the proposed technique to satisfy performance and preserve data privacy through the experimental results.
AUTOMATIC WORD SENSE DISAMBIGUATION ( WSD ) SYSTEM

This paper presents an automatic word sense disambiguation (WSD) system that uses Part-of-Speech (POS) tags along with word classes as the discrete features. Word Classes are derived from the Word Class Assigner using the Word Exchange Algorithm from statistical language processing. Naïve-Bayes classifier is employed from Weka in both the training and testing phases to perform the supervised learning on the standard Senseval-3 data set. Experiments were performing using 10-fold cross-validation on the training set and the training and testing data for training the model and evaluating it. In both experiments, the features will either used separately or combined together to produce the accuracies. Results indicate that word class features did not provide any discrimination for word sense disambiguation. POS tag features produced a small improvement over the baseline. The combination of both word class and POS tag features did not increase the accuracy results. Overall, further study is likely needed to possibly improve the implementation of the word class features in the system.
Answering graph pattern query using incremental views

In recent years, modeling data in graph structure became evident and effective for processing in some of the prominent application areas like social analytics, health care analytics, scientific analytics etc. The key sources of massively scaled data are petascale simulations, experimental devices, the internet and scientific applications. Hence, there is a demand for adapt graph querying techniques on such large graph data. Graphs are pervasive in large scale analytics, facing the new challenge such as data size, heterogeneity, uncertainty and data quality. Traditional graph pattern matching approaches are based on inherent isomorphism and simulation. In real life applications, many of them either fail to capture structural or semantic or both similarities. Moreover, in real life applications data graphs constantly bear modifications with small updates. In response to these challenges, we propose a notion that revises traditional notions to characterize graph pattern matching using graph views. Based on this characterization, we outline an approach that efficiently solve graph pattern queries problem over both static and dynamic real life data graphs.
Giant pituitary tumors: a study based on surgical treatment of 118 cases.

The aim of the study is to analyze the nature, extensions, and dural relationships of hormonally inactive giant pituitary tumors. The relevance of the anatomic relationships to surgery is analyzed.



There were 118 cases of hormonally inactive pituitary tumors analyzed with the maximum dimension of more than 4 cm. These cases were surgically treated in our neurosurgical department from 1995 to 2002. Depending on the anatomic extensions and the nature of their meningeal coverings, these tumors were divided into 4 grades. The grades reflected an increasing order of invasiveness of adjacent dural and arachnoidal compartments. The strategy and outcome of surgery and radiotherapy was analyzed for these 4 groups. Average duration of follow-up was 31 months.



There were 54 giant pituitary tumors, which remained within the confines of sellar dura and under the diaphragma sellae and did not enter into the compartment of cavernous sinus (Grade I). Transgression of the medial wall and invasion into the compartment of the cavernous sinus (Grade II) was seen in 38 cases. Elevation of the dura of the superior wall of the cavernous sinus and extension of this elevation into various compartments of brain (Grade III) was observed in 24 cases. Supradiaphragmatic-subarachnoid extension (Grade IV) was seen in 2 patients. The majority of patients were treated by transsphenoidal route.



Giant pituitary tumors usually have a meningeal cover and extend into well-defined anatomic pathways. Radical surgery by a transsphenoidal route is indicated and possible in Grade I-III pituitary tumors. Such a strategy offers a reasonable opportunity for recovery in vision and a satisfactory postoperative and long-term outcome. Biopsy of the tumor followed by radiotherapy could be suitable for Grade IV pituitary tumors.