nils-herrmann/clean_scirepeval huggingface dataset:
Comparative MiRNA Expressional Profiles and Molecular Networks in Human Small Bowel Tissues of Necrotizing Enterocolitis and Spontaneous Intestinal Perforation
Venue: PloS one
Year: 2015

Necrotizing enterocolitis (NEC) and spontaneous intestinal perforation (SIP) are acute intestinal conditions which could result in mortality and severe morbidity in preterm infants. Our objective was to identify dysregulated micro RNAs (miRNAs) in small bowel tissues of NEC and SIP, and their possible roles in disease pathophysiology.  We performed differential miRNA arrays on tissues of NEC (n 4) SIP (n 4) and surgical control (Surg CTL; n 4) and validated target miRNAs by qPCR (n 10 each group) The association of target miRNAs with 52 dysregulated mRNAs was investigated by bioinformatics on functional and base pair sequence algorithms, and correlation in same tissue samples.  We presented the first miRNA profiles of NEC, SIP and Surg CTL intestinal tissues in preterm infants. Of 28 validated miRNAs, 21 were significantly different between NEC or SIP and Surg CTL. Limited overlapping in the aberrant expression of miRNAs between NEC and SIP indicated their distinct molecular mechanisms. A proposed network of dysregulated miRNA/mRNA pairs in NEC suggested interaction at bacterial receptor TLR4 (miR 31, miR 451, miR 203, miR 4793 3p) mediated via key transcription factors NFKB2 (miR 203) AP 1/FOSL1 (miR 194 3p) FOXA1 (miR 21 3p, miR 431 and miR 1290) and HIF1A (miR 31) and extended downstream to pathways of angiogenesis, arginine metabolism, cell adhesion and chemotaxis, extracellular matrix remodeling, hypoxia/oxidative stress, inflammation and muscle contraction. In contrast, upregulation of miR 451 and miR 223 in SIP suggested modulation of G protein mediated muscle contraction.  The robust response of miRNA dysregulation in NEC and SIP, and concerted involvement of specific miRNAs in the molecular networks indicated their crucial roles in mucosa integrity and disease pathophysiology.
Correct Settings of a Joint Unmanned Aerial Vehicle and Infrared Camera System for the Detection of Faulty Photovoltaic Modules
Venue: IEEE Journal of Photovoltaics
Year: 2021

The technological development of photovoltaic (PV) devices (perovskite based or bifacial modules, etc. has progressed considerably, but the commercial PV modules do not show analogous improvements and their efficiency is still low. Therefore, a diagnostic tool that can check the current operation of installed PV modules and their aging is important. In this scenario, an unmanned aerial vehicle (UAV) equipped with a camera, infrared (IR) camera, or both, represents a new avenue for the fast evaluation of faults for large or not easily accessible PV plants and the discovery of defective PV modules. Thermography has the advantage of not disconnecting the PV system during the inspection. Nevertheless, some specific parameters, such as the emissivity, the reflected temperature, and the resolution, are fixed during the acquisition, even if their values are dependent on the mutual position (distance and angle) between the IR camera and the PV modules. The movement of the UAV, equipped with an IR camera, modifies the position of the IR camera, and due to this movement, the values of the parameters can be incorrect during acquisition, which also results in errors in the radiometric map. In this article, we explore these issues and provide suggestions to ensure the correct acquisition and reading of thermal images of PV modules.
Wild interdisciplinarity: ethnography and computer science
Year: 2018

Drawing on the experiences of a novel collaborative project between sociologists and computer scientists, this paper identifies a set of challenges for fieldwork that are generated by this wild interdisciplinarity.  We argue that similar forms of research, in which social scientists are involved in the deployment of experimental technologies within real world settings, are becoming increasingly prevalent. The fieldwork for the project was highly problematic, with the result that few users of the system were successfully enrolled. We analyse why this was the case, identifying three sets of issues which emerge in the juxtaposition of interdisciplinary collaboration and wild setting. We conclude with a set of recommendations for projects involving technologists and social scientists.
High pressure adaptation of extremophiles and biotechnological applications
Year: 2019

During the last decades, high pressure has gained in importance as physical parameter, not only to study biomolecules, but also for its biotechnological applications. High pressure affects organism's ability to survive by altering most of cell's macromolecules. These effects can be used, for example, to inactivate microorganisms, enhance enzymatic reactions or to modulate cell activities. Moreover, some organisms are capable to grow under high pressures thanks to their adaptation at all cellular levels. Such adaptation confers a wide range of potentially interesting macromolecules still to be discovered. We firstly present the different effects of high pressure on cells and the diverse strategies used by them to cope with this harsh environment. Secondly, we give an overview over biotechnological applications of pressure sensitive and pressure adapted organisms.
Neural Reverse Engineering of Stripped Binaries
Venue: ArXiv
Year: 2019

We address the problem of predicting procedure names in stripped executables which contain no debug information. Predicting procedure names can dramatically ease the task of reverse engineering, saving precious time and human effort. We present a novel approach that leverages static analysis of binaries with encoder decoder based neural networks. The main idea is to use static analysis to obtain enriched representations of API call sites; encode a set of sequences of these call sites; and finally, attend to the encoded sequences while decoding the target name token by token. We evaluate our model by predicting procedure names over $60,000$ procedures in $10,000$ stripped executables. Our model achieves $81.70$ precision and $80.12$ recall in predicting procedure names within GNU packages, and $55.48$ precision and $51.31$ recall in a diverse, cross package, dataset. Comparing to previous approaches, the predictions made by our model are much more accurate and informative.
Canadian Evidence on the Constructive Capitalization of Operating Leases
Year: 2008

One type of relevant ex ante research supporting the accounting standardaEUR setting process is the study of a proposed standard's impact on reported figures. The International Accounting Standards Board recently decided to review the lease accounting standard, which will naturally involve consideration of the G4 1 recommendation to capitalize all noncancellable lease contracts, including operating leases. National evidence of the impact of the G4 1 proposals provides feedback for the international standardaEUR setter. This study developed and used a refined constructive capitalization method, in which companyaEUR specific assumptions aEUR" interest rate, total/expired/remaining lives of leased assets, and tax rate aEUR" were used to compute the impact of operatingaEUR lease capitalization on key financial indicators for a sample of Canadian public companies. The results indicate that capitalizing operating leases would lead to the recognition of important additional assets and liabilities on the balance sheet. It would therefore significantly increase the debtaEUR toaEUR asset ratio and significantly decrease the current ratio. These results were noted across all industry segments in the sample. Income statement effects were generally less material. Significant impacts on return on assets, return on equity, and or earnings per share were noted in only three industry segments: merchandising and lodging, oil and gas, and financial services. Intercompany comparability would not be affected overall nor within industries, because of similar rankings for each financial indicator before and after operatingaEUR lease capitalization.
The Potential of Blockchain within Air Rights Development as a Prevention Measure against Urban Sprawl
Venue: Urban Science
Year: 2019

The rapid rise in urbanization internationally is both driving and stressing our consumption patterns, including that of land use. Urban sprawl is arguably one of the most important threats to human and nature biodiversity given its reliance upon fossil fuel exploitation and consumption. The need for increasing the density of cities is required to contain urban expansion in land size. However, while the footprint density of cities is increasing, vacant plots are prized and rare in most urban areas. Tradable air rights development is seen as a potential solution to provide developers the option of increasing density while encouraging an emerging urban economy. However, the price speculation of air rights is a danger and counter to a fair and inclusive real estate market. This paper proposes a new model that encourages the trading of time sensitive air rights through Smart Contracts in the Blockchain as a means of prevention against urban sprawl.
Quasi Helmholtz Decomposition, Gauss' Laws and Charge Conservation for Finite Element Particle in Cell
Year: 2021

Development of particle in cell methods using finite element based methods (FEMs) have been a topic of renewed interest; this has largely been driven by (a) the ability of finite element methods to better model geometry, (b) better understanding of function spaces that are necessary to represent all Maxwell quantities, and (c) more recently, the fundamental rubrics that should be obeyed in space and time so as to satisfy Gauss' laws and the equation of continuity. In that vein, methods have been developed recently that satisfy these equations and are agnostic to time stepping methods. While is development is indeed a significant advance, it should be noted that implicit FEM transient solvers support an underlying null space that corresponds to a gradient of a scalar potential Ph(r) (or tPh(r) in the case of wave equation solvers) While explicit schemes do not suffer from this drawback, they are only conditionally stable, time step sizes are mesh dependent, and very small. A way to overcome this bottleneck, and indeed, satisfy all four Maxwell's equation is to use a quasi Helmholtz formulation on a tesselation. In the re formulation presented, we strictly satisfy the equation of continuity and Gauss' laws for both the electric and magnetic flux densities. Results demonstrating the efficacy of this scheme will be presented.
Importance of English communication skills
Year: 2016

Communication is a skill which involves systematic and continuous process of speaking, listening and understanding. Most people are born with the physical ability to talk, but we must learn to speak well and communicate effectively. Speaking, listening and our ability to understand verbal and nonverbal cues are the skills by observing other people and modeling our behavior on what we see and perceived. We are also taught some communication skills directly through education. By bringing those skills into practice and getting them evaluated. The face of modern India is changed drastically due to globalization it has brought to India different cultures. In today's world of competition no organizations want to remain local their aim is to expand all over the world.
Assessing the Influence of Spatio Temporal Context for Next Place Prediction using Different Machine Learning Approaches
Venue: ISPRS Int. J. Geo Inf.
Year: 2018

For next place prediction, machine learning methods which incorporate contextual data are frequently used. However, previous studies often do not allow deriving generalizable methodological recommendations, since they use different datasets, methods for discretizing space, scales of prediction, prediction algorithms, and context data, and therefore lack comparability. Additionally, the cold start problem for new users is an issue. In this study, we predict next places based on one trajectory dataset but with systematically varying prediction algorithms, methods for space discretization, scales of prediction (based on a novel hierarchical approach) and incorporated context data. This allows to evaluate the relative influence of these factors on the overall prediction accuracy. Moreover, in order to tackle the cold start problem prevalent in recommender and prediction systems, we test the effect of training the predictor on all users instead of each individual one. We find that the prediction accuracy shows a varying dependency on the method of space discretization and the incorporated contextual factors at different spatial scales. Moreover, our user independent approach reaches a prediction accuracy of around 75% and is therefore an alternative to existing user specific models. This research provides valuable insights into the individual and combinatory effects of model parameters and algorithms on the next place prediction accuracy. The results presented in this paper can be used to determine the influence of various contextual factors and to help researchers building more accurate prediction models. It is also a starting point for future work creating a comprehensive framework to guide the building of prediction models.
Details of human middle ear morphology based on micro CT imaging of phosphotungstic acid stained samples
Venue: Journal of morphology
Year: 2015

A multitude of morphological aspects of the human middle ear (ME) were studied qualitatively and/or quantitatively through the postprocessing and interpretation of micro CT (micro X ray computed tomography) data of six human temporal bones. The samples were scanned after phosphotungstic acid staining to enhance soft tissue contrast. The influence of this staining on ME ossicle configuration was shown to be insignificant. Through postprocessing, the image data were converted into surface models, after which the approaches diverged depending on the topics of interest. The studied topics were: the ME ligaments; morphometric and mechanical parameters of the ossicles relating to inertia and the ossicular lever arm ratio; the morphology of the distal incus; the contact surface areas of the tympanic membrane (TM) and of the stapes footplate; and the thickness of the TM, round window of the cochlea, ossicle joint spaces, and stapedial annular ligament. Some of the resulting insights are relevant in ongoing discussions concerning ME morphology and mechanical functions, while other results provide quantitative data to add to existing data. All findings are discussed in the light of other published data and many are relevant for the construction of mechanical finite element simulations of the ME.  2015.
"Where Do you Want to Take Your Family Firm?" A Theoretical and Empirical Exploratory Study of Family Business Goals
Year: 2017

Family business scholars assume that family business goals represent the nature of the firm's decision making and are driving forces (i.e. antecedents) of family firm behavior, performance, continuity, competitiveness, and sustainability. Without measuring family business goals, family business research specifically, the family business theorizing process is floating in the midst of assumptions used to justify observational descriptive data, such as differences between family and non family firms and differences among various types of family firms. There remains a lack of clarity surrounding the theoretical definition of family business goals and an absence of methodological approaches to make the concept operative. In order to address this gap, this research applies an exploratory step by step methodology that combines both a theoretical and an empirical approach. First, following an inductive literature review, I theorize family business goals as a multidimensional concept combining two scales: economic versus non economic orientation and family versus business orientation. Second, by using a unique Spanish database of family business, I use the partial least squares structural equation modeling method to confirm and extend the proposed theoretical multidimensional concept of family business goals.
Accurate 3D Face Reconstruction With Weakly Supervised Learning: From Single Image to Image Set
Venue: 2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW)
Year: 2019

Recently, deep learning based 3D face reconstruction methods have shown promising results in both quality and efficiency. However, training deep neural networks typically requires a large volume of data, whereas face images with ground truth 3D face shapes are scarce. In this paper, we propose a novel deep 3D face reconstruction approach that 1) leverages a robust, hybrid loss function for weakly supervised learning which takes into account both low level and perception level information for supervision, and 2) performs multi image face reconstruction by exploiting complementary information from different images for shape aggregation. Our method is fast, accurate, and robust to occlusion and large pose. We provide comprehensive experiments on MICC Florence and Facewarehouse datasets, systematically comparing our method with fifteen recent methods and demonstrating its state of the art performance. Code available at https:/github.com/Microsoft/Deep3DFaceReconstruction
On Kim independence
Year: 2017

We study NSOP$_{1} theories. We define Kim independence, which generalizes non forking independence in simple theories and corresponds to non forking at a generic scale. We show that Kim independence satisfies a version of Kim's lemma, local character, symmetry, and an independence theorem and that, moreover, these properties individually characterize NSOP$_{1} theories. We describe Kim independence in several concrete theories and observe that it corresponds to previously studied notions of independence in Frobenius fields and vector spaces with a generic bilinear form.
A modified genetic algorithm for community detection in complex networks
Venue: 2017 International Conference on Algorithms, Methodology, Models and Applications in Emerging Technologies (ICAMMAET)
Year: 2017

Community detection has a very important role in data processing and analysis, which is very hot in recent years. However, traditional algorithms have shortcomings in both time complexity and precision. In this paper, we introduce a Modified Genetic Algorithm (MGA) that with alleles encoding and half uniform crossover to detect community structure. In the algorithm, each allele of the chromosome stands for the community index of the corresponding node. At the same time, half uniform crossover can better prevent the elite individuals from destroying. And we choose modularity function as its fitness function. It does not need to know how many communities the network has. In order to identify our algorithm is effective. We use both artificial random network and real networks to test our algorithm. The experimental results show that the MGA algorithm can be applied to community detection, and its accuracy and time complexity can reach the effect of classical algorithms.
Pengaruh Motivasi terhadap Kinerja Karyawan PT Brawijaya Utama Palembang
Year: 2020

This research aims to investigate the effect of motivation on employees' performance in PT Brawijaya Utama Palembang. Data were collected through questionnaires containing 24 items and analysed with simple linear regression. The results show that the motivation equation on employees' performance is Y 3.326 0.653X. This result states that if the value of motivation is zero, the value of employee performance is 3.326. Every increase in motivation by 1 will increase employees' performance by 0.653. Based on the t test, the value of t stat was 9,164 and the t table was 1,667. The t stat is greater than the t table value of 9,164 1,667 with a sig value of 0,000 (under 0.05) These results indicate that motivation has a significant effect on employees' performance. The coefficient of determination (R2) was obtained at 0.549. It means the contribution of the influence of motivation on the performance of employees of PT Brawijaya Utama Palembang was 54.9% while the remaining 45.1% was influenced by other variables that were not captured in this study.
Critical challenges in the system development of direct alcohol fuel cells as portable power supplies: An overview
Year: 2019

Direct alcohol fuel cells (DAFCs) are considered a reasonable alternative power source because alcohol has a much higher energy density than hydrogen. Most DAFC development has focused on small portable application by using passive systems. DAFCs with active feed systems have appeared as potential portable power sources for larger applications, as they are easily handled, simple systems with smaller volumes than polymer electrolyte membrane fuel cells (PEMFCs) A general active DAFC system consists of a fuel and oxidant supplying system, product management and fuel concentration control. However, system development and commercialization are constrained by various critical challenges. This paper highlights the critical challenges of the fuel cell system rather than fundamental problems in the membrane electrode assembly (MEA) including fuel feed fluctuation, contaminant poisoning, two phase flow, low power density, and heat and water management.
De Facto Detrebling: The Rush to Settlement in Antitrust Class Action Litigation
Year: 2008

Antitrust law provides that successful private plaintiffs are entitled to treble damages. Despite this, in antitrust class action litigation, courts have subtly dismantled the treble damage regime by manipulating the standard for reviewing proposed settlements. Federal law requires judicial approval of class action settlements in order to ensure that the class members' interests are adequately protected. However, following the Second Circuit's 1974 Grinnell opinion, federal courts decline to consider the trebling of damages when estimating the value of class claims extinguished by antitrust class action settlements. Despite its longevity, the Grinnell rule has received no academic attention. This is surprising because the Grinnell court based its decision on a misreading of its source material. More importantly, the Grinnell rule undermines both the compensatory and deterrent functions of antitrust law.
Patterns and drivers of fungal disease communities on Arabica coffee along a management gradient
Year: 2020

Plants, including those managed by humans, are often attacked by multiple diseases. Yet, most studies focus on single diseases, even if the disease dynamics of multiple species is more interesting from a farmers' perspective. Moreover, most studies are from single management systems, although it is valuable to understand how diseases are distributed across broad management gradients, especially in cases where less intensive management also provides biodiversity values in the landscape. To understand the spatial dynamics and drivers of diseases across such a broad management gradient, we assessed four major fungal diseases on Arabica coffee (Coffea arabica) at 60 sites in southwestern Ethiopia along a gradient from only little managed wild coffee in the forest understory to intensively managed coffee plantations. We found that environmental and management factors related to disease incidence and severity differed strongly among the four fungal diseases. Coffee leaf rust (Hemileia vastatrix) and Armillaria root rot (Armillaria mellea) were more severe in intensively managed sites, whereas coffee berry disease (Colletotrichum kahawae) and wilt disease (Gibberella xylarioides) were more severe in less managed sites. Among sites, incidence and severity of the four fungal diseases poorly correlated with each other. Within sites, however, shrubs that were severely attacked by coffee leaf rust also had high levels of berry disease symptoms. A better understanding of disease dynamics is important for providing management recommendations that benefit smallholder farmers, but also to evaluate possibilities for maintaining biodiversity values in the landscape related to shade cover complexity and wild coffee genetic variation.