nils-herrmann/clean_scirepeval huggingface dataset:
Modeling and Stability Analysis of Islanded DC Microgrids Under Droop Control

The stability of dc microgrids (MGs) depends on the control strategy adopted for each mode of operation. In an islanded operation mode, droop control is the basic method for bus voltage stabilization when there is no communication among the sources. In this paper, it is shown the consequences of droop implementation on the voltage stability of dc power systems, whose loads are active and nonlinear, e.g., constant power loads. The set of parallel sources and their corresponding transmission lines are modeled by an ideal voltage source in series with an equivalent resistance and inductance. This approximate model allows performing a nonlinear stability analysis to predict the system qualitative behavior due to the reduced number of differential equations. Additionally, nonlinear analysis provides analytical stability conditions as a function of the model parameters and it leads to a design guideline to build reliable (MGs) based on safe operating regions.
Deregulated activation of matriptase in breast cancer cells

Matriptase is an epithelial-derived, cell surface serine protease. This protease activates hepatocyte growth factor (HGF) and urokinase plasminogen activator (uPA), two proteins thought to be involved in the growth and motility of cancer cells, particularly carcinomas, and in the vascularization of tumors. Thus, matriptase may play an important role in the progression of carcinomas, such as breast cancer. We examined the regulation of activation of matriptase in human breast cancer cells, in comparison to non-transformed mammary epithelial cells 184A1N4 and MCF-10A. Results clearly indicated that unlike non-transformed mammary epithelial cells, breast cancer cells do not respond to the known activators of matriptase, serum and sphingosine 1-phosphate (S1P). Similar levels of activated matriptase were detected in breast cancer cells, grown in the presence or absence of S1P. However, up to five-fold higher levels of activated matriptase were detected in the conditioned media from the cancer cells grown in the absence of serum and S1P, when compared to non-transformed mammary epithelial cells. S1P also induces formation of cortical actin structures in non-transformed cells, but not in breast cancer cells. These results show that in non-transformed cells, S1P induces a rearrangement of the actin cytoskeleton and stimulates proteolytic activity on cell surfaces. In contrast, S1P treatment of breast cancer cells does not activate matriptase, and instead these cells constitutively activate the protease. In addition, breast cancer cells respond differently to S1P in terms of the regulation of actin cytoskeletal structures. Matriptase and its cognate inhibitor, HGF activator inhibitor 1 (HAI-1) colocalize on the cell periphery of breast cancer cells and form stable complexes in the extracellular milieu, suggesting that the inhibitor serves to prevent undesired proteolysis in these cells. Finally, we demonstrate that treatment of T-47D cells with epidermal growth factor (EGF), which promotes cell ruffling, stimulates increased accumulation of activated matriptase at the sites of membrane ruffling, suggesting a possible functional role at these sites.
Improving focus and context awareness in interactive visualization of time lines

This paper presents an analysis and empirical evaluation of techniques developed to support focus and context awareness in tasks involving visualization of time lines. It focuses on time lines that display discrete events and their temporal relationships. The most common form of representation for such time lines is the Gantt chart. Although ubiquitous in event visualization and project planning applications, Gantt charts are inherently space-consuming, and suffer from shortcomings in providing focus and context awareness when a large number of tasks and events needs to be displayed. In an attempt to address this problem, we implemented and adapted a number of focus and context awareness techniques for an interactive task scheduling system in combination with the standard Gantt chart and an alternative space-filling mosaic approach to time line visualization. A controlled user trial compared user performance at interpreting representations of hierarchical task scheduling, assessing different methods across various conditions resulting from interactive explorations of the Gantt and the mosaic interfaces. Results suggested a number of possible improvements to these interactive visualization techniques. The implementation of some of these improvements is also presented and discussed.
Accelerating literature curation with text-mining tools: a case study of using PubTator to curate genes in PubMed abstracts

Today's biomedical research has become heavily dependent on access to the biological knowledge encoded in expert curated biological databases. As the volume of biological literature grows rapidly, it becomes increasingly difficult for biocurators to keep up with the literature because manual curation is an expensive and time-consuming endeavour. Past research has suggested that computer-assisted curation can improve efficiency, but few text-mining systems have been formally evaluated in this regard. Through participation in the interactive text-mining track of the BioCreative 2012 workshop, we developed PubTator, a PubMed-like system that assists with two specific human curation tasks: document triage and bioconcept annotation. On the basis of evaluation results from two external user groups, we find that the accuracy of PubTator-assisted curation is comparable with that of manual curation and that PubTator can significantly increase human curatorial speed. These encouraging findings warrant further investigation with a larger number of publications to be annotated.
Generative Steganography by Sampling

In this paper, a new data-driven information hiding scheme called generative steganography by sampling (GSS) is proposed. The stego is directly sampled by a powerful generator without an explicit cover. Secret key shared by both parties is used for message embedding and extraction, respectively. Jensen-Shannon Divergence is introduced as new criteria for evaluation of the security of the generative steganography. Based on these principles, a simple practical generative steganography method is proposed using semantic image inpainting. Experiments demonstrate the potential of the framework through qualitative and quantitative evaluation of the generated stego images.
Remodeling of the Z-Ring Nanostructure during the Streptococcus pneumoniae Cell Cycle Revealed by Photoactivated Localization Microscopy

Ovococci form a morphological group that includes several human pathogens (enterococci and streptococci). Their shape results from two modes of cell wall insertion, one allowing division and one allowing elongation. Both cell wall synthesis modes rely on a single cytoskeletal protein, FtsZ. Despite the central role of FtsZ in ovococci, a detailed view of the in vivo nanostructure of ovococcal Z-rings has been lacking thus far, limiting our understanding of their assembly and architecture. We have developed the use of photoactivated localization microscopy (PALM) in the ovococcus human pathogen Streptococcus pneumoniae by engineering spDendra2, a photoconvertible fluorescent protein optimized for this bacterium. Labeling of endogenously expressed FtsZ with spDendra2 revealed the remodeling of the Z-ring's morphology during the division cycle at the nanoscale level. We show that changes in the ring's axial thickness and in the clustering propensity of FtsZ correlate with the advancement of the cell cycle. In addition, we observe double-ring substructures suggestive of short-lived intermediates that may form upon initiation of septal cell wall synthesis. These data are integrated into a model describing the architecture and the remodeling of the Z-ring during the cell cycle of ovococci.



The Gram-positive human pathogen S. pneumoniae is responsible for 1.6 million deaths per year worldwide and is increasingly resistant to various antibiotics. FtsZ is a cytoskeletal protein polymerizing at midcell into a ring-like structure called the Z-ring. FtsZ is a promising new antimicrobial target, as its inhibition leads to cell death. A precise view of the Z-ring architecture in vivo is essential to understand the mode of action of inhibitory drugs (see T. den Blaauwen, J. M. Andreu, and O. Monasterio, Bioorg Chem 55:27-38, 2014, doi:10.1016/j.bioorg.2014.03.007, for a review on FtsZ inhibitors). This is notably true in ovococcoid bacteria like S. pneumoniae, in which FtsZ is the only known cytoskeletal protein. We have used superresolution microscopy to obtain molecular details of the pneumococcus Z-ring that have so far been inaccessible with conventional microscopy. This study provides a nanoscale description of the Z-ring architecture and remodeling during the division of ovococci.
Data utilization for medical decision making at the time of patient admission to ICU.

Information overload in electronic medical records can impede providers' ability to identify important clinical data and may contribute to medical error. An understanding of the information requirements of ICU providers will facilitate the development of information systems that prioritize the presentation of high-value data and reduce information overload. Our objective was to determine the clinical information needs of ICU physicians, compared to the data available within an electronic medical record.



Prospective observational study and retrospective chart review.



Three ICUs (surgical, medical, and mixed) at an academic referral center.



Newly admitted ICU patients and physicians (residents, fellows, and attending staff).



The clinical information used by physicians during the initial diagnosis and treatment of admitted patients was captured using a questionnaire. Clinical information concepts were ranked according to the frequency of reported use (primary outcome) and were compared to information availability in the electronic medical record (secondary outcome). Nine hundred twenty-five of 1,277 study questionnaires (408 patients) were completed. Fifty-one clinical information concepts were identified as being useful during ICU admission. A median (interquartile range) of 11 concepts (6-16) was used by physicians per patient admission encounter with four used greater than 50% of the time. Over 25% of the clinical data available in the electronic medical record was never used, and only 33% was used greater than 50% of the time by admitting physicians.



Physicians use a limited number of clinical information concepts at the time of patient admission to the ICU. The electronic medical record contains an abundance of unused data. Better electronic data management strategies are needed, including the priority display of frequently used clinical concepts within the electronic medical record, to improve the efficiency of ICU care.
Maximum reach envelope for the seated and standing male and female for industrial workstation design.

Maximum reach envelopes for the 5th, 50th and 95th percentile reach lengths of males and females in seated and standing work positions were determined. The use of a computerized potentiometric measurement system permitted functional reach measurement in 15 min for each subject. The measurement system captured reach endpoints in a dynamic mode while the subjects were describing their maximum reach envelopes. An unbiased estimate of the true reach distances was made through a systematic computerized data averaging process. The maximum reach envelope for the standing position was significantly (p<0.05) larger than the corresponding measure in the seated position for both the males and females. The average reach length of the female was 13.5% smaller than that for the corresponding male. Potential applications of this research include designs of industrial workstations, equipment, tools and products.
Overview of BioNLP Shared Task 2011

The BioNLP Shared Task 2013 is the third edition of the BioNLP Shared Task series that is a community-wide effort to address fine-grained, structural information extraction from biomedical literature.  Six main tasks were proposed. 38 final submissions were received, from 22 teams. The results show advances in the state of the art and demonstrate that extraction methods can be successfully generalized in various aspects.
56 Gb/s PAM-4 optical receiver frontend in an advanced FinFET process

This paper presents a 56Gb/s PAM-4 optical receiver analog frontend circuits which consists of three inverter stages TIA with resistive feedback in the first and third stages. An adaptively-tuned continuous-time linear equalizer (CTLE) is cascaded after the TIA for improved sensitivity and bandwidth. The overall gain is controlled by an automatic gain control (AGC) circuits to avoid the large input optical power saturates the TIA, thus distorting the PAM-4 signals. The frontend receiver circuits is designed in an advanced FinFET technology and overall gain achieves 68 dBO with a 22 GHz bandwidth. The simulated input referred current rms noise is 2.86 μA. Total chip power is 6.3 mW from a 0.83 V supply. The chip active area is 150μm × 100 μm.
Open-TEE -- An Open Virtual Trusted Execution Environment

Hardware-based Trusted Execution Environments (TEEs) are widely deployed in mobile devices. Yet their use has been limited primarily to applications developed by the device vendors. Recent standardization of TEE interfaces by GlobalPlatform (GP) promises to partially address this problem by enabling GP-compliant trusted applications to run on TEEs from different vendors. Nevertheless ordinary developers wishing to develop trusted applications face significant challenges. Access to hardware TEE interfaces are difficult to obtain without support from vendors. Tools and software needed to develop and debug trusted applications may be expensive or non-existent. In this paper, we describe Open-TEE, a virtual, hardware-independent TEE implemented in software. Open-TEE conforms to GP specifications. It allows developers to develop and debug trusted applications with the same tools they use for developing software in general. Once a trusted application is fully debugged, it can be compiled for any actual hardware TEE. Through performance measurements and a user study we demonstrate that Open-TEE is efficient and easy to use. We have made Open-TEE freely available as open source.
Integrating urban energy simulation in a parametric environment : a Grasshopper interface for

The increasing popularity of parametric design tools goes hand in hand with the use of building performance simulation (BPS) tools from the early design phase. However, current methods require a significant computational time and a high number of parameters as input, as they are based on traditional BPS tools conceived for detailed building design phase. Their application to the urban scale is hence difficult. As an alternative to the existing approaches, we developed an interface to CitySim, a validated building simulation tool adapted to urban scale assessments, bundled as a plug-in for Grasshopper, a popular parametric design platform. On the one hand, CitySim allows faster simulations and requires fewer parameters than traditional BPS tools, as it is based on algorithms providing a good trade-off between the simulations requirements and their accuracy at the urban scale; on the other hand, Grasshopper allows the easy manipulation of building masses and energy simulation parameters through semi-automated parametric
Developing PDA for low-bitrate low-delay video delivery

Pervasive wireless multimedia applications often require Personal Digital Assistants (PDAs) for processing and playback. The capability of PDAs, however, are generally much lower than desktop PCs. When these devices are used to play back video delivered over a network from a desktop server, their buffers can easily overflow, seriously degrading the video quality. In this paper, we report our implementation of some special stream processing techniques to deal with the capability mismatch between a PC and PDAs for low-delay live video streaming. These techniques are, the Selective Packet Drop (SPD) algorithm, the Game API (GAPI) optimization and the speed adaptation algorithm. All of them can be easily implemented. We show that our system provides much better video quality than systems without our techniques.
Pinnacle Point Cave 13B (Western Cape Province, South Africa) in context: The Cape Floral kingdom, shellfish, and modern human origins.

Genetic and anatomical evidence suggests that Homo sapiens arose in Africa between 200 and 100ka, and recent evidence suggests that complex cognition may have appeared between ~164 and 75ka. This evidence directs our focus to Marine Isotope Stage (MIS) 6, when from 195-123ka the world was in a fluctuating but predominantly glacial stage, when much of Africa was cooler and drier, and when dated archaeological sites are rare. Previously we have shown that humans had expanded their diet to include marine resources by ~164ka (±12ka) at Pinnacle Point Cave 13B (PP13B) on the south coast of South Africa, perhaps as a response to these harsh environmental conditions. The associated material culture documents an early use and modification of pigment, likely for symbolic behavior, as well as the production of bladelet stone tool technology, and there is now intriguing evidence for heat treatment of lithics. PP13B also includes a later sequence of MIS 5 occupations that document an adaptation that increasingly focuses on coastal resources. A model is developed that suggests that the combined richness of the Cape Floral Region on the south coast of Africa, with its high diversity and density of geophyte plants and the rich coastal ecosystems of the associated Agulhas Current, combined to provide a stable set of carbohydrate and protein resources for early modern humans along the southern coast of South Africa during this crucial but environmentally harsh phase in the evolution of modern humans. Humans structured their mobility around the use of coastal resources and geophyte abundance and focused their occupation at the intersection of the geophyte rich Cape flora and coastline. The evidence for human occupation relative to the distance to the coastline over time at PP13B is consistent with this model.
Privacy-Preserving Data Mining

Privacy-preserving data mining (PPDM) refers to the area of data mining that seeks to safeguard sensitive information from unsolicited or unsanctioned disclosure. Most traditional data mining techniques analyze and model the data set statistically, in aggregated form, while privacy preservation is primarily concerned with protecting against disclosure of individual data records. This domain separation points to the technical feasibility of PPDM. Historically, issues related to PPDM were first studied by the national statistical agencies interested in collecting private social and economical data, such as census and tax records, and making it available for analysis by public servants, companies, and researchers. Building accurate socioeconomical models is vital for business planning and public policy. Yet, there is no way of knowing in advance what models may be needed, nor is it feasible for the statistical agency to perform all data processing for everyone, playing the role of a trusted third party. Instead, the agency provides the data in a sanitized form that allows statistical processing and protects the privacy of individual records, solving a problem known as privacypreserving data publishing. For a survey of work in statistical databases, see Adam and Wortmann (1989) and Willenborg and de Waal (2001). The term privacy-preserving data mining was introduced in the papers Agrawal and Srikant (2000) and Lindell and Pinkas (2000). These papers considered two fundamental problems of PPDM: privacy-preserving data collection and mining a data set partitioned across several private enterprises. Agrawal and Srikant devised a randomization algorithm that allows a large number of users to contribute their private records for efficient centralized data mining while limiting the disclosure of their values; Lindell and Pinkas invented a cryptographic protocol for decision tree construction over a data set horizontally partitioned between two parties. These methods were subsequently refined and extended by many researchers worldwide. Other areas that influence the development of PPDM include cryptography and secure multiparty computation (Goldreich, 2004; Stinson, 2006), database query auditing for disclosure Chapter LVI Privacy-Preserving Data Mining
Dynamic programming algorithms for haplotype block partitioning: applications to human chromosome 21 haplotype data

Recent studies have shown that the human genome has a haplotype block structure such that it can be divided into discrete blocks of limited haplotype diversity. Patil et al.  and Zhang et al.  developed algorithms to partition haplotypes into blocks with minimum number of tag SNPs for the entire chromosome. However, it is not clear how to partition haplotypes into blocks with restricted number of SNPs when only limited resources are available. In this paper, we first formulated this problem as finding a block partition with a fixed number of tag SNPs that can cover the maximal percentage of a genome. Then we solved it by two dynamic programming algorithms, which are fairly flexible to take into account the knowledge of functional polymorphism. We applied our algorithms to the published SNP data of human chromosome 21 combining with the functional information of these SNPs and demonstrated the effectiveness of them. Statistical investigation of the relationship between the starting points of a block partition and the coding and non-coding regions illuminated that the SNPs at these starting points are not significantly enriched in coding regions. We also developed an efficient algorithm to find all possible long local maximal haplotypes across a subset of samples. After applying this algorithm to the human chromosome 21 haplotype data, we found that samples with long local haplotypes are not necessarily globally similar.
Face Parsing via a Fully-Convolutional Continuous CRF Neural Network

In this work, we address the face parsing task with a Fully-Convolutional continuous CRF Neural Network (FCCNN) architecture. In contrast to previous face parsing methods that apply region-based subnetwork hundreds of times, our FCCNN is fully convolutional with high segmentation accuracy. To achieve this goal, FC-CNN integrates three subnetworks, a unary network, a pairwise network and a continuous Conditional Random Field (C-CRF) network into a unified framework. The high-level semantic information and low-level details across different convolutional layers are captured by the convolutional and deconvolutional structures in the unary network. The semantic edge context is learnt by the pairwise network branch to construct pixel-wise affinity. Based on a differentiable superpixel pooling layer and a differentiable C-CRF layer, the unary network and pairwise network are combined via a novel continuous CRF network to achieve spatial consistency in both training and test procedure of a deep neural network. Comprehensive evaluations on LFW-PL and HELEN datasets demonstrate that FC-CNN achieves better performance over the other state-of-arts for accurate face labeling on challenging images.