nils-herrmann/clean_scirepeval huggingface dataset:
Densely Connected Convolutional Neural Network for Multi-purpose Image Forensics under Anti-forensic Attacks

Multiple-purpose forensics has been attracting increasing attention worldwide. However, most of the existing methods based on hand-crafted features often require domain knowledge and expensive human labour and their performances can be affected by factors such as image size and JPEG compression. Furthermore, many anti-forensic techniques have been applied in practice, making image authentication more difficult. Therefore, it is of great importance to develop methods that can automatically learn general and robust features for image operation detectors with the capability of countering anti-forensics. In this paper, we propose a new convolutional neural network (CNN) approach for multi-purpose detection of image manipulations under anti-forensic attacks. The dense connectivity pattern, which has better parameter efficiency than the traditional pattern, is explored to strengthen the propagation of general features related to image manipulation detection. When compared with three state-of-the-art methods, experiments demonstrate that the proposed CNN architecture can achieve a better performance (i.e., with a 11% improvement in terms of detection accuracy under anti-forensic attacks). The proposed method can also achieve better robustness against JPEG compression with maximum improvement of 13% on accuracy under low-quality JPEG compression.
The lasso-loop, lasso-mattress and simple-cinch stitch for arthroscopic rotator cuff repair: are there biomechanical differences?

Various stitching techniques have been described to facilitate arthroscopic repair of rotator cuff tears. The aim of the present study was to compare the biomechanical properties of the lasso-loop, lasso-mattress and simple-cinch stitch for rotator cuff repair. Twelve infraspinatus tendons were harvested from sheep and split in half. The tendons were randomized into three different stitch configuration groups for biomechanical testing: lasso-loop, lasso-mattress and simple-cinch stitch. Each specimen was first cyclically loaded on a universal materials testing machine under force control from 5 to 30 N at 0.25 Hz for twenty cycles. Then, each specimen was loaded to failure under displacement control at a rate of 1 mm/s. Cyclic elongation, peak-to-peak displacement and ultimate tensile load were reported as mean ± standard error and compared using one way analysis of variance. The type of failure was recorded. No differences in cyclic elongation (1.31 ± 0.09 mm for the simple-cinch vs. 1.49 ± 0.07 mm for the lasso-mattress vs. 1.61 ± 0.09 mm for the lasso-loop stitch, p = 0.063) or peak-to-peak displacement (0.58 ± 0.04 mm for the simple-cinch, 0.50 ± 0.03 mm for the lasso-mattress and 0.62 ± 0.06 mm for the lasso-loop stitch, p = 0.141) were seen between all tested stitch configurations. In the load-to-failure test, the simple cinch stitch (149.38 ± 11.89 N) and the lasso-mattress (149.38 ± 10.33 N) stitch demonstrated significantly higher ultimate load than the lasso-loop stitch (65.88 ± 4.75 N, p < 0.001). All stitch configurations failed with suture pull out. The lasso-mattress and the simple-cinch stitch showed similar biomechanical properties with significant higher tensile loads needed for failure than the lasso-loop stitch.
CT angiography: injection and acquisition technique.

CT scanner technology is continuously evolving, with scan times becoming shorter with each scanner generation. Achieving adequate arterial opacification synchronized with CT data acquisition is becoming increasingly difficult. A fundamental understanding of early arterial contrast medium dynamics is thus of utmost importance for the design of CT scanning and injection protocols for current and future cardiovascular CT applications. Arterial enhancement is primarily controlled by the iodine flux (injection flow rate) and the injection duration versus a patient's cardiac output and local downstream physiology. The technical capabilities of modern CT equipment require precise scan timing. Together with automated tube current modulation and weight-based injection protocols, both radiation exposure and contrast medium enhancement can be individualized.
Monolithic LTCC SiP transmitter for 60GHz wireless communication terminals

We demonstrate a 36 times 12 times 0.9mm3 sized compact monolithic LTCC SiP transmitter (Tx) for 60GHz-band wireless communication terminal applications. Five GaAs MMICs including mixer, driver amplifier, power amplifier and two of frequency doublers have been integrated onto LTCC multilayer circuit which embeds a stripline BPF and a microstrip patch antenna. A novel CPW-to-stripline transition has been devised integrating air-cavities to minimize the associated attenuation. The fabricated transmitter achieves an output of 9dBm at a RF frequency of 60.4GHz, an IF frequency of 2.4GHz, and a LO frequency of 58GHz. The up-conversion gain is 11.2dB; while the LO signal is suppressed below 33.4dBc, and the spurious signal is also suppressed below 27.4dBc. This is the first report on the LTCC SiP transmitter integrating both a BPF and an antenna. A 60 GHz communication was demonstrated
Advances in paper-based point-of-care diagnostics.

Advanced diagnostic technologies, such as polymerase chain reaction (PCR) and enzyme-linked immunosorbent assay (ELISA), have been widely used in well-equipped laboratories. However, they are not affordable or accessible in resource-limited settings due to the lack of basic infrastructure and/or trained operators. Paper-based diagnostic technologies are affordable, user-friendly, rapid, robust, and scalable for manufacturing, thus holding great potential to deliver point-of-care (POC) diagnostics to resource-limited settings. In this review, we present the working principles and reaction mechanism of paper-based diagnostics, including dipstick assays, lateral flow assays (LFAs), and microfluidic paper-based analytical devices (μPADs), as well as the selection of substrates and fabrication methods. Further, we report the advances in improving detection sensitivity, quantification readout, procedure simplification and multi-functionalization of paper-based diagnostics, and discuss the disadvantages of paper-based diagnostics. We envision that miniaturized and integrated paper-based diagnostic devices with the sample-in-answer-out capability will meet the diverse requirements for diagnosis and treatment monitoring at the POC.
Geo-topo maps: hybrid visualization of movement data over building floor plans and maps

We demonstrate how movements of multiple people or objects within a building can be displayed on a network representation of the building, where nodes are rooms and edges are doors. Our representation shows the direction of movements between rooms and the order in which rooms are visited, while avoiding occlusion or overplotting when there are repeated visits or multiple moving people or objects. We further propose the use of a hybrid visualization that mixes geospatial and topological (network-based) representations, enabling focus-in-context and multi-focal visualizations. An experimental comparison found that the topological representation was significantly faster than the purely geospatial representation for three out of four tasks.
Pornography , Rape , and the Internet

The arrival of the internet caused a large decline in both the pecuniary and non-pecuniary costs of accessing pornography. Using state-level panel data from 1998-2003, I find that the arrival of the internet was associated with a reduction in rape incidence. However, growth in internet usage had no apparent effect on other crimes. Moreover, when I disaggregate the rape data by offender age, I find that the effect of the internet on rape is concentrated among those for whom the internet-induced fall in the non-pecuniary price of pornography was the largest – men ages 15-19, who typically live with their parents. These results, which suggest that pornography and rape are substitutes, are in contrast with most previous literature. However, earlier population-level studies do not control adequately for many omitted variables, including the age distribution of the population, and most laboratory studies simply do not allow for potential substitutability between pornography and rape.
Intrinsic Light Field Images

We present a method to automatically decompose a light field into its intrinsic shading and albedo components. Contrary to previous work targeted to 2D single images and videos, a light field is a 4D structure that captures non-integrated incoming radiance over a discrete angular domain. This higher dimensionality of the problem renders previous state-of-the-art algorithms impractical either due to their cost of processing a single 2D slice, or their inability to enforce proper coherence in additional dimensions. We propose a new decomposition algorithm that jointly optimizes the whole light field data for proper angular coherency. For efficiency, we extend Retinex theory, working on the gradient domain, where new albedo and occlusion terms are introduced. Results show our method provides 4D intrinsic decompositions difficult to achieve with previous state-of-the-art algorithms. We further provide a comprehensive analysis and comparisons with existing intrinsic image/video decomposition methods on light field images.
Resilient Datacenter Load Balancing in the Wild SIGCOMM ’

Production datacenters operate under various uncertainties such as tra c dynamics, topology asymmetry, and failures. Therefore, datacenter load balancing schemes must be resilient to these uncertainties; i.e., they should accurately sense path conditions and timely react to mitigate the fallouts. Despite signi cant e orts, prior solutions have important drawbacks. On the one hand, solutions such as Presto and DRB are oblivious to path conditions and blindly reroute at xed granularity. On the other hand, solutions such as CONGA and CLOVE can sense congestion, but they can only reroute when owlets emerge; thus, they cannot always react timely to uncertainties. To make things worse, these solutions fail to detect/handle failures such as blackholes and random packet drops, which greatly degrades their performance. In this paper, we introduce Hermes, a datacenter load balancer that is resilient to the aforementioned uncertainties. At its heart, Hermes leverages comprehensive sensing to detect path conditions including failures unattended before, and it reacts using timely yet cautious rerouting. Hermes is a practical edge-based solution with no switch modi cation. We have implemented Hermes with commodity switches and evaluated it through both testbed experiments and large-scale simulations. Our results show that Hermes achieves comparable performance to CONGA and Presto in normal cases, and well handles uncertainties: under asymmetries, Hermes achieves up to 10% and 20% better ow completion time (FCT) than CONGA and CLOVE; under switch failures, it outperforms all other schemes by over 32%.
Grouping Synonymous Sentences from a Parallel Corpus

Recently, natural language processing researches have focused on data or processing techniques for paraphrasing. Unfortunately, however, we have little data for paraphrasing. There are some research reports on collecting synonymous expressions with parallel corpus, though no suitable corpus for collecting a set of paraphrases is yet available. Therefore, we obtain a few variations of expression in paraphrase sets when we tried to apply this method with a parallel corpus. In this paper, we propose a grouping method based on the basic idea of grouping synonymous sentences related to the translation recursively, and decompose incorrect groups using the DMdecomposition algorithm. The incorrect groups include expressions that cannot be paraphrased because some words or expressions have different meanings in different situations. We discuss our method and experimental results with respect to BTEC, which is a multilingual parallel corpus.
Summarization with a Joint Model for Sentence Extraction and Compression

Text summarization is one of the oldest problems in natural language processing. Popular approaches rely on extracting relevant sentences from the original documents. As a side effect, sentences that are too long but partly relevant are doomed to either not appear in the final summary, or prevent inclusion of other relevant sentences. Sentence compression is a recent framework that aims to select the shortest subsequence of words that yields an informative and grammatical sentence. This work proposes a one-step approach for document summarization that jointly performs sentence extraction and compression by solving an integer linear program. We report favorable experimental results on newswire data.
Pathological burst fracture in the cervical spine with negative red flags: a case report.

To report on a case of a pathological burst fracture in the cervical spine where typical core red flag tests failed to identify a significant lesion, and to remind chiropractors to be vigilant in the recognition of subtle signs and symptoms of disease processes.



A 61-year-old man presented to a chiropractic clinic with neck pain that began earlier that morning. After a physical exam that was relatively unremarkable, imaging identified a burst fracture in the cervical spine.



The patient was sent by ambulance to the hospital where he was diagnosed with multiple myeloma. No medical intervention was performed on the fracture.



The patient's initial physical examination was largely unremarkable, with an absence of clinical red flags. The screening tools were non-diagnostic. Pain with traction and the sudden onset of symptoms prompted further investigation with plain film imaging of the cervical spine. This identified a pathological burst fracture in the C4 vertebrae.
Sequence to Sequence Modeling for User Simulation in Dialog Systems

User simulators are a principal offline method for training and evaluating human-computer dialog systems. In this paper, we examine simple sequence-to-sequence neural network architectures for training end-to-end, natural language to natural language, user simulators, using only raw logs of previous interactions without any additional human labelling. We compare the neural network-based simulators with a language model (LM)-based approach for creating natural language user simulators. Using both an automatic evaluation using LM perplexity and a human evaluation, we demonstrate that the sequence-tosequence approaches outperform the LM-based method. We show correlation between LM perplexity and the human evaluation on this task, and discuss the benefits of different neural network architecture variations.
Annual Iron Loss Associated with Hemodialysis.

In order to keep up the optimal iron status in chronic hemodialysis patients, it is important to know how much iron is lost due to hemodialysis. Residual blood associated with the hemodialysis procedure together with blood sampling inevitably causes the loss of iron in chronic hemodialysis patients. Recent advances in hemodialysis techniques might have reduced this complication. In this cross-sectional study, we directly measured total iron loss by hemodialysis.



Two hundred thirty-nine patients who received chronic hemodialysis at Otowa Memorial Hospital were enrolled; 65.7% of patients were men, and mean age was 67 ± 6.4 years (mean ± SD) and 43.2% were diabetic. Residual blood in blood tubing set and dialyzer after rinse back with saline was collected and homogenized. The iron content including free, protein-bound and heme iron was measured using an atomic absorption spectrometry.



The mean iron content in residual blood was 1,247.3 ± 796.2 µg (mean ± SD) and the median was 1,002 µg (95% CI 377.6-3,461.6 µg), indicating 160.8 mg (95% CI 58.9-540.0 mg) iron loss annually when hemodialysis was performed 156 times a year. Fifty milliliter whole blood for monthly blood test and another 2 ml of whole blood lost by paracentesis at every dialysis session contains 228.6 and 118.9 mg iron at 11 g/dl hemoglobin, respectively. Therefore, an annual total iron loss due to hemodialysis comes to 508.3 mg (95% CI 406.4-887.5 mg).



Five hundred milligram of annual iron supplementation might be sufficient to maintain iron status in hemodialysis patients, which is less than the dose recommended as 1,000-2,000 mg a year. Further study will be required to verify this iron supplementation dosage with recent hemodialysis procedure.
Resistance training with soy vs whey protein supplements in hyperlipidemic males

Most individuals at risk for developing cardiovascular disease (CVD) can reduce risk factors through diet and exercise before resorting to drug treatment. The effect of a combination of resistance training with vegetable-based (soy) versus animal-based (whey) protein supplementation on CVD risk reduction has received little study. The study's purpose was to examine the effects of 12 weeks of resistance exercise training with soy versus whey protein supplementation on strength gains, body composition and serum lipid changes in overweight, hyperlipidemic men.



Twenty-eight overweight, male subjects (BMI 25-30) with serum cholesterol >200 mg/dl were randomly divided into 3 groups (placebo (n = 9), and soy (n = 9) or whey (n = 10) supplementation) and participated in supervised resistance training for 12 weeks. Supplements were provided in a double blind fashion.



All 3 groups had significant gains in strength, averaging 47% in all major muscle groups and significant increases in fat free mass (2.6%), with no difference among groups. Percent body fat and waist-to-hip ratio decreased significantly in all 3 groups an average of 8% and 2%, respectively, with no difference among groups. Total serum cholesterol decreased significantly, again with no difference among groups.



Participation in a 12 week resistance exercise training program significantly increased strength and improved both body composition and serum cholesterol in overweight, hypercholesterolemic men with no added benefit from protein supplementation.
A Comparison of Techniques to Find Mirrored Hosts on the WWW

Extraction-Transformation-Loading (ETL) and Data Cleani ng tools are pieces of software responsible for the extraction of data from several sources, their clean ing, customization and insertion into a data warehouse. To deal with the complexity and efficiency of the t ransformation and cleaning tasks we have developed a tool, namely ARKTOS, capable of modeling and executing practical scenarios, by providing explicit primitives for the capturing of common tasks. ARKTOS provides three ways to describe such a scenario, including a graphical point-and-click front en d and two declarative languages: XADL (an XML variant), which is more verbose and easy to read and SADL ( an SQL-like language) which has a quite compact syntax and is, thus, easier for authoring.
Hock immunization: a humane alternative to mouse footpad injections.

Footpad injection is a commonly used immunization method in mice. Being relatively easy to do with well-characterized lymphatic drainage, it has become a very useful immunization protocol to study local immune responses in draining lymph nodes. However, its disadvantages include use of only hind feet as a routine site of immunization since mice use their fore feet for food handling, and exacerbation of inflammation and swelling at the injection site leading to unrelieved pain and distress since feet are weight-bearing structures. With increasingly stringent Institutional guidelines for animal manipulations, there is increasing need for more humane protocols. A novel immunization protocol involving injection into the hock, the lateral tarsal region just above the ankle, a non-weight bearing structure draining to the same lymph node as the footpad, retains the advantages of footpad immunization without its drawbacks. This study, comparing immune responses between footpad and hock immunization in six different inbred mouse strains to two different protein antigens and a heat-killed bacterium, shows that hock immunization is a better alternative to footpad immunization, inducing comparable immune responses and being considerably more humane.
Nebulized 0.5, 2.5 and 5 ml l-epinephrine for post-extubation stridor in children: a prospective, randomized, double-blind clinical trial

Nebulized l-epinephrine has been recommended for the treatment of viral croup. However, the few studies assessing its effect on post-extubation stridor (PES) have shown conflicting results. We compared the efficacy and safety of nebulized l-epinephrine at three different doses for the treatment of PES. We conducted a prospective, randomized, double-blind trial including all consecutive children with a PES score of ≥4 (Westley score). The primary efficacy outcome was change in PES score at 40 min. A reduction of ≥2 points in stridor score was defined as clinically significant. A total of 96 patients were randomly assigned to receive one of three doses of nebulized l-epinephrine upon achieving a PES score of 4 or more following extubation. Stridor score and vital signs were recorded before treatment, and at 20, 40, 60 and 180 min after nebulization. Baseline characteristics were similar among all study groups. No significant difference was detected among the treatments based on change in Westley score by intent-to-treat analysis. In addition, the difference in the number of patients who clinically improved among the treatment groups was not significant (p = 0.54). Patients receiving 5 ml nebulized epinephrine had a significant increase of systolic and diastolic blood pressure at 40 and 180 min. Nebulized l-epinephrine at doses of 0.5, 2.5 and 5 ml demonstrated a lack of dose response in effect on PES and a modestly clinically significant increase in undesired side effects (heart rate and blood pressure) at higher doses.
FotoFile: A Consumer Multimedia Organization and Retrieval System

FotoFile is an experimental system for multimediaorganization and retrieval, based upon the design goal of makingmultimedia content accessible to non-expert users. Search andretrieval are done in terms that are natural to the task. Thesystem blends human and automatic annotation methods. It extendstextual search, browsing, and retrieval technologies to supportmultimedia data types.
An Incremental Document Clustering Algorithm Based on a Hierarchical Agglomerative Approach

Document clustering is an automatic grouping of text documents into clusters so that documents within a cluster have high similarity in comparison to one another, but are dissimilar to documents in other clusters. Unlike document classification (Wang, Zhou, and He, 2001), no labeled documents are provided in clustering; hence, clustering is also known as unsupervised learning. Hierarchical document clustering organizes clusters into a tree or a hierarchy that facilitates browsing. The parent-child relationship among the nodes in the tree can be viewed as a topic-subtopic relationship in a subject hierarchy such as the Yahoo! directory. This chapter discusses several special challenges in hierarchical document clustering: high dimensionality, high volume of data, ease of browsing, and meaningful cluster labels. State-ofthe-art document clustering algorithms are reviewed: the partitioning method (Steinbach, Karypis, and Kumar, 2000), agglomerative and divisive hierarchical clustering (Kaufman and Rousseeuw, 1990), and frequent itemset-based hierarchical clustering (Fung, Wang, and Ester, 2003). The last one, which was recently developed by the authors, is further elaborated since it has been specially designed to address the hierarchical document clustering problem.