nils-herrmann/clean_scirepeval huggingface dataset:
Effect of Intra-articular Injection of AOD9604 with or without Hyaluronic Acid in Rabbit Osteoarthritis Model.

To investigate the effects of AOD9604 intra-articular injections with or without hyaluronic acid (HA) in a collagenase-induced knee osteoarthritis (OA) rabbit model.



Mature New Zealand white rabbits (n=32) were randomly administered 2 mg collagenase type II twice in each knee joint. Weekly injections of 0.6 mL saline (Group 1), 6 mg HA (Group 2), 0.25 mg AOD9604 (Group 3), and 0.25 mg AOD9604 with 6 mg HA (Group 4) were administered for 4-7 weeks after the first intra-articular collagenase injection. The degree of cartilage degeneration was assessed using morphological and histopathological findings, and the degree of lameness was observed at 8 weeks after the first collagenase injection.



Mean gross morphological and histopathological scores were significantly higher in Group 1 than in Groups 2, 3, and 4, and the scores were significantly lower in Group 4 than in Groups 2 and 3. The lameness period in Group 4 was significantly shorter than those in Groups 1, 2, and 3. The lameness period in Group 1 was significantly longer than those in Groups 2 and 3.



Intra-articular AOD9604 injections using ultrasound guidance enhanced cartilage regeneration, and combined AOD9604 and HA injections were more effective than HA or AOD9604 injections alone in the collagenase-induced knee OA rabbit model.
Application of Network Calculus to Guaranteed Service Networks

We use recent network calculus results to study some properties of lossless multiplexing as it may be used in guaranteed service networks. We call network calculus a set of results that apply min-plus algebra to packet networks. We provide a simple proof that shaping a traffic stream to conform to a burstiness constraint preserves the original constraints satisfied by the traffic stream We show how all rate-based packet schedulers can be modeled with a simple rate latency service curve. Then we define a general form of deterministic effective bandwidth and equivalent capacity. We find that call acceptance regions based on deterministic criteria (loss or delay) are convex, in contrast to statistical cases where it is the complement of the region which is convex. We thus find that, in general, the limit of the call acceptance region based on statistical multiplexing when the loss probability target tends to 0 may be strictly larger than the call acceptance region based on lossless multiplexing. Finally, we consider the problem of determining the optimal parameters of a variable bit rate (VBR) connection when it is used as a trunk, or tunnel, given that the input traffic is known. We find that there is an optimal peak rate for the VBR trunk, essentially insensitive to the optimization criteria. For a linear cost function, we find an explicit algorithm for the optimal remaining parameters of the VBR trunk.
Online bagging and boosting

Bagging and boosting are two of the most well-known ensemble learning methods due to their theoretical performance guarantees and strong experimental results. However, these algorithms have been used mainly in batch mode, i.e., they require the entire training set to be available at once and, in some cases, require random access to the data. In this paper, we present online versions of bagging and boosting that require only one pass through the training data. We build on previously presented work by describing some theoretical results. We also compare the online and batch algorithms experimentally in terms of accuracy and running time.
Modeling ETL Process for Data Warehouse: An Exploratory Study

The data warehouse facilitates knowledge workers in decision making process. A good DW design can actually reduce the report processing time but, it requires substantial efforts in ETL design and implementation. In this paper, the authors have focused on the working of Extraction, Transformation and Loading. The focus has also been laid on the data quality problem which in result leads to falsification of analysis based on that data. The authors have also analyzed and compared various ETL modeling processes. So this study would be substantially fruitful for understanding various approaches of ETL modeling in data warehousing.
3D cGAN based cross-modality MR image synthesis for brain tumor segmentation

Different modalities of magnetic resonance imaging (MRI) can indicate tumor-induced tissue changes from different perspectives, thus benefit brain tumor segmentation when they are considered together. Meanwhile, it is always interesting to examine the diagnosis potential from single modality, considering the cost of acquiring multi-modality images. Clinically, T1-weighted MRI is the most commonly used MR imaging modality, although it may not be the best option for contouring brain tumor. In this paper, we investigate whether synthesizing FLAIR images from T1 could help improve brain tumor segmentation from the single modality of T1. This is achieved by designing a 3D conditional Generative Adversarial Network (cGAN) for FLAIR image synthesis and a local adaptive fusion method to better depict the details of the synthesized FLAIR images. The proposed method can effectively handle the segmentation task of brain tumors that vary in appearance, size and location across samples.
Is the Implicit Association Test a Valid and Valuable Measure of Implicit Consumer Social Cognition ?

This article discusses the need for more satisfactory implicit measures in consumer psychology and assesses the theoretical foundations, validity, and value of the Implicit Association Test (IAT) as a measure of implicit consumer social cognition. Study 1 demonstrates the IAT’s sen­ sitivity to explicit individual differences in brand attitudes, ownership, and usage frequency, and shows their correlations with IAT-based measures of implicit brand attitudes and brand re­ lationship strength. In Study 2, the contrast between explicit and implicit measures of attitude toward the ad for sportswear advertisements portraying African American (Black) and Euro­ pean American (White) athlete–spokespersons revealed different patterns of responses to ex­ plicit and implicit measures in Black and White respondents. These were explained in terms of self-presentation biases and system justification theory. Overall, the results demonstrate that the IAT enhances our understanding of consumer responses, particularly when consumers are either unable or unwilling to identify the sources of influence on their behaviors or opinions.
Power Operation in ISD: Technological Frames Perspectives

This paper investigates the power operation in information system development (ISD) processes. Due to the fact that key actors in different departments possess different professional knowledge, their different contexts lead to some employees supporting IS, while others resist it to achieve their goals. We aim to interpret these power operations in ISD from the theory of technological frames. This study is based on qualitative data collected from KaoKang (pseudonym), a port authority in Taiwan. We attempt to understand the situations of different key actors (e.g. top manager, MIS professionals, employees of DP-1 division, consultants of KaoKang, and customers (outside users)) who wield power in ISD in different situations. In this respect, we interpret the data using a technological frame. Finally, we aim to gain fresh insight into power operation in ISD from this perspective.
UAV for 3 D mapping applications : a review

Unmanned Aerial Vehicle (UAV) platforms are nowadays a valuable source of data for inspection, surveillance, mapping and 3D modeling issues. As UAVs can be considered as a lowcost alternative to the classical manned aerial photogrammetry, new applications in the shortand close-range domain are introduced. Rotary or fixed wing UAVs, capable of performing the photogrammetric data acquisition with amateur or SLR digital cameras, can fly in manual, semiautomated and autonomous modes. Following a typical photogrammetric workflow, 3D results like Digital Surface or Terrain Models (DTM/DSM), contours, textured 3D models, vector information, etc. can be produced, even on large areas. The paper reports the state of the art of UAV for Geomatics applications, giving an overview of different UAV platforms, applications and case studies, showing also the latest developments of UAV image processing. New perspectives are also addressed.
The COMPOSE API for the internet of things

The COMPOSE project aims to provide an open Marketplace for the Internet of Things as well as the necessary platform to support it. A necessary component of COMPOSE is an API that allows things, COMPOSE users and the platform to communicate. The COMPOSE API allows for things to push data to the platform, the platform to initiate asynchronous actions on the things, and COMPOSE users to retrieve and process data from the things. In this paper we present the design and implementation of the COMPOSE API, as well as a detailed description of the main key requirements that the API must satisfy. The API documentation and the source code for the platform are available online.
Data management and transfer in high-performance computational grid environments

An emerging class of data-intensive applications involve the geographically dispersed extraction of complex scientific information from very large collections of measured or computed data. Such applications arise, for example, in experimental physics, where the data in question is generated by accelerators, and in simulation science, where the data is generated by supercomputers. So-called Data Grids provide essential infrastructure for such applications, much as the Internet provides essential services for applications such as e-mail and the Web. We describe here two services that we believe are fundamental to any Data Grid: reliable, high-speed transport and replica management. Our high-speed transport service, GridFTP, extends the popular FTP protocol with new features required for Data Grid applications, such as striping and partial file access. Our replica management service integrates a replica catalog with GridFTP transfers to provide for the creation, registration, location, and management of dataset replicas. We present the design of both services and also preliminary performance results. Our implementations exploit security and other services provided by the Globus Toolkit.
Virtual and Real World Adaptation for Pedestrian Detection

Pedestrian detection is of paramount interest for many applications. Most promising detectors rely on discriminatively learnt classifiers, i.e., trained with annotated samples. However, the annotation step is a human intensive and subjective task worth to be minimized. By using virtual worlds we can automatically obtain precise and rich annotations. Thus, we face the question: can a pedestrian appearance model learnt in realistic virtual worlds work successfully for pedestrian detection in real-world images? Conducted experiments show that virtual-world based training can provide excellent testing accuracy in real world, but it can also suffer the data set shift problem as real-world based training does. Accordingly, we have designed a domain adaptation framework, V-AYLA, in which we have tested different techniques to collect a few pedestrian samples from the target domain (real world) and combine them with the many examples of the source domain (virtual world) in order to train a domain adapted pedestrian classifier that will operate in the target domain. V-AYLA reports the same detection accuracy than when training with many human-provided pedestrian annotations and testing with real-world images of the same domain. To the best of our knowledge, this is the first work demonstrating adaptation of virtual and real worlds for developing an object detector.
A CMOS-compatible silicon photonic platform for high-speed integrated optoelectronics

We have developed a CMOS-compatible Silicon-on-Insulator photonic platform featuring active components such as pi-n and photoconductive (MIM) Ge-on-Si detectors, p-i-n ring and Mach-Zehnder modulators, and traveling-wave modulators based on a p-n junction driven by an RF transmission line. We have characterized the yield and uniformity of the performance through automated cross-wafer testing, demonstrating that our process is reliable and scalable. The entire platform is capable of more than 40 GB/s data rate. Fabricated at the IME/A-STAR foundry in Singapore, it is available to the worldwide community through OpSIS, a successful multi-project wafer service based at the University of Delaware. After exposing the design, fabrication and performance of the most advanced platform components, we present our newest results obtained after the first public run. These include low loss passives (Y-junctions: 0.28 dB; waveguide crossings: 0.18 dB and cross-talk -41±2 dB; non-uniform grating couplers: 3.2±0.2 dB). All these components were tested across full 8” wafers and exhibited remarkable uniformity. The active devices were improved from the previous design kit to exhibit 3dB bandwidths ranging from 30 GHz (modulators) to 58 GHz (detectors). We also present new packaging services available to OpSIS users: vertical fiber coupling and edge coupling.
Securing cloud infrastructure against co-resident DoS attacks using game theoretic defense mechanisms

Evolution in cloud services and infrastructure has been constantly reshaping the way we conduct business and provide services in our day to day lives. Tools and technologies created to improve such cloud services can also be used to impair them. By using generic tools like nmap, hping and wget, one can estimate the placement of virtual machines in a cloud infrastructure with a high likelihood. Moreover, such knowledge and tools can also be used by adversaries to further launch various kinds of attacks. In this paper we focus on one such specific kind of attack, namely a denial of service (DoS), where an attacker congests a bottleneck network channel shared among virtual machines (VMs) coresident on the same physical node in the cloud infrastructure. We evaluate the behavior of this shared network channel using Click modular router on DETER testbed. We illustrate that game theoretic concepts can be used to model this attack as a two-player game and recommend strategies for defending against such attacks.
PPARγ Pro12Ala interacts with fat intake for obesity and weight loss in a behavioural treatment based on the Mediterranean diet.

The goal of this study was to examine whether the Pro12Ala polymorphism of peroxisome proliferator-activated receptor γ (PPARγ) is associated with insulin resistance, obesity and weight loss and to analyze potential interactions between fat intake and PPARγ polymorphism in a Spanish overweight/obese population.



We recruited 1465 subjects enrolled in a behavioural treatment program for obesity based on a Mediterranean diet, which included the following: dietary treatment, physical activity, nutritional education and behavioral techniques. A significant association was found between PPARγ2 Pro12Ala genotype and plasma insulin concentration and homeostasis model assessment insulin resistance. Subjects with the Ala12 genotype had lower insulin levels than those with the Pro12Pro genotype. We detected a gene-diet interaction between the PPARγ Pro12Ala polymorphism and MUFA for BMI and body fat. Furthermore, we detected an interaction between the PPARγ Pro12Ala polymorphism and fat intake for total weight loss (p<0.001). When total fat intake was high, Ala12-carriers exhibited a significantly lower percentage of total weight loss than major-allele-carriers (p=0.037).



Data are consistent with previous results showing a protective role for the Ala12 allele against insulin resistance, and replicate an earlier study that detected an interaction between dietary MUFA and PPARγ2 for BMI. Our detection of a gene-diet interaction between PPARγ Pro12Ala and fat intake for weight loss may explain previous discrepancies among different studies.
Asynchronous Adiabatic Logic

Power clock generators (PCGs) are the prevalent overhead for the adiabatic systems and mutilate all the low-power advantage from the adiabatic logic part by consuming a large portion of the total power in the clock generation circuitry (Arsalan and Shams, 2005). In addition to the PCG issues, routing multiple clock phases for adiabatic circuits is not very convenient and raises a number of cost, performance and viability issues. To get rid of the problems related to clock generation and synchronous clock routing, a new solution namely asynchronous adiabatic logic (AAL) is proposed to combing the benefits of the adiabatic logic circuits with that of asynchronous logic systems. Going asynchronous not only eliminates the need of PCGs, hence all the problems associated with the generation and routing of the clocks, it also bring all the advantages intrinsically associated with an asynchronous design such as low power and reliable logical operation.
Effect of high hydrostatic pressure on antioxidant content of 'Ataulfo' mango during postharvest maturation

(006063) 1 Laboratorio Integral de Investigación en Alimentos – LIIA, Instituto Tecnológico de Tepic – ITT, Av. Tecnológico, 2595, CP 63175, Tepic, Nayarit, México, e-mail: efimontalvo@gmail.com 2 Dirección General de Innovación Tecnológica, Centro de Excelencia, Universidad Autónoma de Tamaulipas – UAT, Ciudad Victoria, Tamaulipas, México 3 Centro de Investigación en Ciencia Aplicada y Tecnología Avanzada – CICATA, Instituto Politécnico Nacional – IPN, Querétaro, Querétaro, México *Corresponding author Effect of high hydrostatic pressure on antioxidant content of ‘Ataulfo’ mango during postharvest maturation Viviana Guadalupe ORTEGA1, José Alberto RAMÍREZ2, Gonzalo VELÁZQUEZ3, Beatriz TOVAR1, Miguel MATA1, Efigenia MONTALVO1
Phrase-Based Presentation Slides Generation for Academic Papers

Automatic generation of presentation slides for academic papers is a very challenging task. Previous methods for addressing this task are mainly based on document summarization techniques and they extract document sentences to form presentation slides, which are not well-structured and concise. In this study, we propose a phrase-based approach to generate well-structured and concise presentation slides for academic papers. Our approach first extracts phrases from the given paper, and then learns both the saliency of each phrase and the hierarchical relationship between a pair of phrases. Finally a greedy algorithm is used to select and align the salient phrases in order to form the well-structured presentation slides. Evaluation results on a real dataset verify the efficacy of our proposed approach.
Exercise manages fatigue during breast cancer treatment: a randomized controlled trial.

Fatigue is the most prevalent and debilitating symptom experienced by breast cancer patients receiving adjuvant chemotherapy or radiation therapy and few evidence-based treatments are available to manage this distressing side-effect. The purpose of this multi-institutional randomized controlled trial was to determine the effects of exercise on fatigue levels during treatment for breast cancer. Sedentary women (N=119) with Stage 0-III breast cancer receiving outpatient adjuvant chemotherapy or radiation therapy were randomized to a home-based moderate-intensity walking exercise program or to usual care for the duration of their cancer treatment. Of participants randomized to exercise, 72% adhered to the exercise prescription; 61% of the usual care group adhered. The intention-to-treat analysis revealed no group differences in part because of a dilution of treatment effect as 39% of the usual care group exercised and 28% of the exercise group did not. When exercise participation was considered using the data analysis method of instrumental variables with principal stratification, a clinically important and statistically significant (p=0.03) effect of exercise on pretest-to-posttest change in fatigue levels was demonstrated. Adherence to a home-based moderate-intensity walking exercise program may effectively mitigate the high levels of fatigue prevalent during cancer treatment.
A 12-b 10-GS/s Interleaved Pipeline ADC in 28-nm CMOS Technology

A 12-bit 10-GS/s interleaved (IL) pipeline analog-to-digital converter (ADC) is described in this paper. The ADC achieves a signal to noise and distortion ratio (SNDR) of 55 dB and a spurious free dynamic range (SFDR) of 66 dB with a 4-GHz input signal, is fabricated in the 28-nm CMOS technology, and dissipates 2.9 W. Eight pipeline sub-ADCs are interleaved to achieve 10-GS/s sample rate, and mismatches between sub-ADCs are calibrated in the background. The pipeline sub-ADCs employ a variety of techniques to lower power, like avoiding a dedicated sample-and-hold amplifier (SHA-less), residue scaling, flash background calibration, dithering and inter-stage gain error background calibration. A push–pull input buffer optimized for high-frequency linearity drives the interleaved sub-ADCs to enable >7-GHz bandwidth. A fast turn-ON bootstrapped switch enables 100-ps sampling. The ADC also includes the ability to randomize the sub-ADC selection pattern to further reduce residual interleaving spurs.
Predictive Effects of Novelty Measured by Temporal Embeddings on the Growth of Scientific Literature

Novel scientific knowledge is constantly produced by the scientific community. Understanding the level of novelty characterized by scientific literature is key for modeling scientific dynamics and analyzing the growth mechanisms of scientific knowledge. Metrics derived from bibliometrics and citation analysis were effectively used to characterize the novelty in scientific development. However, time is required before we can observe links between documents such as citation links or patterns derived from the links, which makes these techniques more effective for retrospective analysis than predictive analysis. In this study, we present a new approach to measuring the novelty of a research topic in a scientific community over a specific period by tracking semantic changes of the terms and characterizing the research topic in their usage context. The semantic changes are derived from the text data of scientific literature by temporal embedding learning techniques. We validated the effects of the proposed novelty metric on predicting the future growth of scientific publications and investigated the relations between novelty and growth by panel data analysis applied in a largescale publication dataset (MEDLINE/PubMed). Key findings based on the statistical investigation indicate that the novelty metric has significant predictive effects on the growth of scientific literature and the predictive effects may last for more than ten years. We demonstrated the effectiveness and practical implications of the novelty metric in three case studies. ∗jiangen.he@drexel.edu, chaomei.chen@drexel.edu. Department of Information Science, Drexel University. 1 ar X iv :1 80 1. 09 12 1v 1 [ cs .D L ] 2 7 Ja n 20 18