nils-herrmann/clean_scirepeval huggingface dataset:
Coverless image steganography based on DenseNet feature mapping
Venue: EURASIP J. Image Video Process.
Year: 2020

Since the concept of coverless information hiding was proposed, it has been greatly developed due to its effectiveness of resisting the steganographic tools. Most existing coverless image steganography (CIS) methods achieve excellent robustness under non geometric attacks. However, they do not perform well under some geometric attacks. Towards this goal, a CIS algorithm based on DenseNet feature mapping is proposed. Deep learning is introduced to extract high dimensional CNN features which are mapped into hash sequences. For the sender, a binary tree hash index is built to accelerate index speed of searching hidden information and DenseNet hash sequence, and then, all matched images are sent. For the receiver, the secret information can be recovered successfully by calculating the DenseNet hash sequence of the cover image. During the whole steganography process, the cover images remain unchanged. Experimental results and analysis show that the proposed scheme has better robust compared with the state of the art methods under geometric attacks.
The importance of uncertainties in scenario analyses A study on future ecosystem service delivery in Flanders.
Venue: The Science of the total environment
Year: 2016

Land use is rapidly changing and is significantly affecting ecosystem service delivery all around the world. The socio economic context and political choices largely determine land use change. This land use change, driven by socio economic pressures, will impact diverse elements of the environment including, for example, air quality, soil properties, water infiltration and food and wood production, impacts that can be linked to the provisioning of ecosystem services. To gain more insight into the effects of alternative socio economic developments on ecosystem service delivery, land use change models are being coupled to ecosystem service delivery models to perform scenario analyses. Although the uncertainty of the results of these kind of scenario analyses are generally far from negligible, studies rarely take them into account. In this study, a cellular automaton land use change model is coupled to Bayesian belief network ecosystem service delivery models to facilitate the study of error propagation in scenario analysis. The proposed approach is applied to model the impact of alternative socio economic developments on ecosystem service delivery in Flanders, Belgium and to assess the impact of land use allocation uncertainty on the uncertainty associated to future ecosystem service delivery. Results suggest that taking into account uncertainties may have an effect on policy recommendations that come out of the scenario analysis. However, in this study, uncertainties in the applied ecosystem service models were dominant, reducing the importance of accounting for land use allocation uncertainty.
Retrieval guided Dialogue Response Generation via a Matching to Generation Framework
Venue: EMNLP
Year: 2019

End to end sequence generation is a popular technique for developing open domain dialogue systems, though they suffer from the safe response problem. Researchers have attempted to tackle this problem by incorporating generative models with the returns of retrieval systems. Recently, a skeleton then response framework has been shown promising results for this task. Nevertheless, how to precisely extract a skeleton and how to effectively train a retrieval guided response generator are still challenging. This paper presents a novel framework in which the skeleton extraction is made by an interpretable matching model and the following skeleton guided response generation is accomplished by a separately trained generator. Extensive experiments demonstrate the effectiveness of our model designs.
Delving into the Antiurolithiatic Potential of Tribulus terrestris Extract Through In Vivo Efficacy and Preclinical Safety Investigations in Wistar Rats
Venue: Scientific Reports
Year: 2019

Modern treatment interventions for kidney stones are wrought with side effects, hence the need for alternative therapies such as plant based medicines. We have previously documented through in vitro studies that statistically optimized aqueous extract of Tribulus terrestris (Zygophyllaceae family) possesses antiurolithic and antioxidant potential. This provides strong scientific foundation to conduct in vivo efficacy and preclinical safety studies to corroborate and lend further proof to its ability to prevent and cure kidney stones. The preventive and curative urolithiatic efficacy in experimentally induced nephrolithiatic Wistar rats, along with preclinical toxicity was evaluated following oral administration of statistically optimized aqueous extract of T. terrestris. Treatment showed augmented renal function, restoration of normal renal architecture and increase in body weight. Microscopic analysis of urine revealed excretion of small sized urinary crystals, demonstrating that treatment potentially modulated the morphology of renal stones. Tissue enzymatic estimation affirmed the antioxidant efficacy of treatment with reduced free radical generation. Significant upregulation of p38MAPK at both the gene and protein level was noted in hyperoxaluric group and interestingly treatment reversed it. Acute oral toxicity study established the Median Lethal Dose (LD50) to be greater than 2000 mg/kg body weight (b.wt. No observed adverse effect level (NOAEL) by repeated oral toxicity for 28 days at 750 mg/kg b.wt. was noted. This study lends scientific evidence to the safe, preventive and curative potential of statistically optimized aqueous extract of T. terrestris at a dose of 750 mg/kg b.wt. and suggests that the extract shows promise as a therapeutic antiurolithic agent.
Towards a Holistic Approach to Designing Theory based Mobile Health Interventions
Venue: ArXiv
Year: 2017

Increasing evidence has shown that theory based health behavior change interventions are more effective than non theory based ones. However, only a few segments of relevant studies were theory based, especially the studies conducted by non psychology researchers. On the other hand, many mobile health interventions, even those based on the behavioral theories, may still fail in the absence of a user centered design process. The gap between behavioral theories and user centered design increases the difficulty of designing and implementing mobile health interventions. To bridge this gap, we propose a holistic approach to designing theory based mobile health interventions built on the existing theories and frameworks of three categories: (1) behavioral theories (e.g. the Social Cognitive Theory, the Theory of Planned Behavior, and the Health Action Process Approach) (2) the technological models and frameworks (e.g. the Behavior Change Techniques, the Persuasive System Design and Behavior Change Support System, and the Just in Time Adaptive Interventions) and (3) the user centered systematic approaches (e.g. the CeHRes Roadmap, the Wendel's Approach, and the IDEAS Model) This holistic approach provides researchers a lens to see the whole picture for developing mobile health interventions.
Women, Gender, and Everyday Social Transformation in India
Year: 2015

agenda has increasingly been co opted into the war on terror, and questions need to be raised about the dangers of a military interventionism that is justified by reference to women's rights, an inherent danger in securitising these issues (see Pratt and RichterDevroe 2014; Wibben 2011) At the same time, the WPS agenda continues to thrive thanks largely to activists pushing for their countries to develop NAPs and using the leverage, however small, that the UNSC resolutions provide in their activism beyond NAPs. Indeed, while 'for many of us, these resolutions do not go far enough to confront patriarchy and militarism, and instead keeps us inside the same economic global system that contributes to these conflicts' as Rosalind Boyd (p. 11) notes, 'the UN remains the only body where we are able to address our concerns to all member states' This book is an important contribution to thinking deeper and acting smarter as far as gender responsive human security is concerned and it challenges us to broaden our analysis to think beyond those neat distinctions between peace and war or security and economics, that limit our analyses and actions. With concrete lessons learned and clearly articulated recommendations for future action, the book is an important addition to the excellent Ashgate 'Gender in a Global/Local World' series, and a must read for practitioners and scholars grappling with the security development nexus.
Factors determining behavioral intentions to use Islamic financial technology
Year: 2020

This paper aims to provide an improved understanding of the influential factors on behavioral intentions towards Islamic financial technology usage in Indonesia, for all types of financial technology services including payment, peer to peer lending and crowdfunding both simultaneously and partial for each service to enhance the financial inclusion.  This study adopted structural equation modelling using the partial least squares approach to test the hypotheses. The questionnaire was distributed through an online survey and collected 1,262 responses based on the purposive sampling technique.  The results demonstrate that the latent variables; planned behavior, acceptance model and use of technology have a significant impact on encouraging behavioral intentions to use Islamic financial technology. The acceptance model is the most significant factor.  This study is conducted in Indonesia, therefore, the results cannot be generalized to other countries. However, this paper provides important strategic guidelines for policy makers in designing a framework to enhance the development of Islamic financial technology and to achieve financial inclusion. It is suggested that future studies includes samples from financial technology users in different countries.  This study adds to the literature especially on the factors affecting behavioral intentions to use Islamic financial technology. There are limited studies concerning to this topic, especially for Indonesia. The unique feature of this study is the use of a large primary dataset that covers most provinces in Indonesia. Furthermore, this study focusing on three types of Islamic financial technology: payment, peer to peer lending and crowdfunding.
Power Brokers in a Punjabi Village: A Case Study of Power Manifestation
Year: 2017

The purpose of paper was to study the role of power brokers in the Punjabi community to see how they replaced the cult ural institution of leadership in the name of deraydar. The paper tr i s to bring forth the factors that made these power brokers influenti al and how did the traditional leader faded away from the cultural life of the villages. The paper also describes the sources of p ower that these brokers enjoy at local level and the manipulative s trategies that are consciously held to maintain the social control thr ough reciprocity towards group allies and coercive tactics towards t he opponents. The paper also discusses political set up of the vi llage to see how political set up revolves around the pressure group s of village. How are these formed as the source of power due to whic h ea h group tried to manipulate benefits using its political in fluence, links, and relationships, etc. The study also looks into how t hese politically influential groups try to over throw their opponent groups.
A roadmap for graphene
Venue: Nature
Year: 2012

Recent years have witnessed many breakthroughs in research on graphene (the first two dimensional atomic crystal) as well as a significant advance in the mass production of this material. This one atom thick fabric of carbon uniquely combines extreme mechanical strength, exceptionally high electronic and thermal conductivities, impermeability to gases, as well as many other supreme properties, all of which make it highly attractive for numerous applications. Here we review recent progress in graphene research and in the development of production methods, and critically analyse the feasibility of various graphene applications.
Microvisor: A Runtime Architecture for Thermal Management in Chip Multiprocessors
Venue: Trans. High Perform. Embed. Archit. Compil.
Year: 2011

In today's high performance computing environment, power density issues are at the forefront of design constraints. Many platforms integrate a diverse set of processing cores on the same die to fit small form factors. Due to the design limitations of using expensive cooling solutions, such complex chip multiprocessors require an architectural solution to mitigate thermal problems. Many of the current systems deploy voltage/frequency scaling to address thermal emergencies, either within the operating system or in hardware. These techniques have certain limitations in terms of response lag, scalability, cost and being reactive. In this paper, we present an alternative thermal management system to address these limitations, based on virtual machine concept that uses a runtime layer of software (microvisor) to manage the computational demands of threads to the thermal constraints of cores. Our results show that a predictive, targeted, and localized response to thermal events improves performance by an average of 21% over counterpart operating system and hardware control theoretic implementations.
New approach of ECG denoising based on 1 D double density complex DWT and SBWT
Venue: Comput. methods Biomech. Biomed. Eng. Imaging Vis.
Year: 2020

In this paper we propose a new ECG denoising approach based on the application of double density complex denoising method in the stationary bionic wavelet transform domain. This approach consists at the first step in applying the to the noisy ECG signal in order to obtain two noisy coefficients and The latter is an approximation coefficient and is a detail one. The latter is then denoised using Soft thresholding for obtaining a denoised coefficient, The double density complex denoising method is applied to and we obtain a denoised coefficient, The denoised ECG signal is finally obtained from the application of the inverse of the to and This proposed technique is evaluated and compared to the double density complex denoising one, the denoising technique based on Wavelets and Hidden Markov Models, the technique based on Non Local Means and our previous proposed approach based on and (translation invariant forward wavelet transform) The simulation results obtained from the computations of SNR (ratio) MAE (mean absolute error) PSNR (peak SNR) and CC (cross correlation) show that the proposed technique outperforms the other techniques used in our evaluation
Cancer cell imaging and photothermal therapy in the near infrared region by using gold nanorods.
Venue: Journal of the American Chemical Society
Year: 2006

Due to strong electric fields at the surface, the absorption and scattering of electromagnetic radiation by noble metal nanoparticles are strongly enhanced. These unique properties provide the potential of designing novel optically active reagents for simultaneous molecular imaging and photothermal cancer therapy. It is desirable to use agents that are active in the near infrared (NIR) region of the radiation spectrum to minimize the light extinction by intrinsic chromophores in native tissue. Gold nanorods with suitable aspect ratios (length divided by width) can absorb and scatter strongly in the NIR region (650 900 nm) In the present work, we provide an in vitro demonstration of gold nanorods as novel contrast agents for both molecular imaging and photothermal cancer therapy. Nanorods are synthesized and conjugated to anti epidermal growth factor receptor (anti EGFR) monoclonal antibodies and incubated in cell cultures with a nonmalignant epithelial cell line (HaCat) and two malignant oral epithelial cell lines (HOC 313 clone 8 and HSC 3) The anti EGFR antibody conjugated nanorods bind specifically to the surface of the malignant type cells with a much higher affinity due to the overexpressed EGFR on the cytoplasmic membrane of the malignant cells. As a result of the strongly scattered red light from gold nanorods in dark field, observed using a laboratory microscope, the malignant cells are clearly visualized and diagnosed from the nonmalignant cells. It is found that, after exposure to continuous red laser at 800 nm, malignant cells require about half the laser energy to be photothermally destroyed than the nonmalignant cells. Thus, both efficient cancer cell diagnostics and selective photothermal therapy are realized at the same time.
Evolving Behaviour Dependent Strategies in Agent Negotiations
Venue: ECAL
Year: 2013

We use genetic algorithms to evolve trading strategies for iterative bilateral negotiations between buyers and sellers. In contrast to previous work we evolve purely reactive strategies that base decisions on memories of behaviour in previous negotiation rounds. We find that simulations lead to three main types of behaviour: (i) cooperative outcomes in which bargaining leads to an agreement and equal sharing of profits, (ii) uncooperative outcomes in which negotiations are not successful and (iii) outcomes in which one party profits at the expense of the other. The frequencies of each type of behaviour vary when the probability for negotiations to terminate is changed, confirming our hypothesis that cooperation should decrease as this break off probability increases. Comparisons of the results to tit for tat (TFT) strategies and previous research on the iterated prisoner's dilemma (IPD) are used to understand simulation results, and we observe the emergence of TFT behaviour during periods of agent cooperation.
Profiling of immune cancer interactions at the single cell level using a microfluidic well array.
Venue: The Analyst
Year: 2020

Cancer immunotherapy has achieved great success in hematological cancers. However, immune cells are a highly heterogeneous population and can vary highly in clonal expansion, migration and function status, making it difficult to evaluate and predict patient response to immune therapy. Conventional technologies only yield information on the average population information of the treatment, masking the heterogeneity of the individual T cell activation status, the formation of immune synapse, as well as the efficacy of tumor cell killing at the single cell level. To fully interrogate these single cell events in detail, herein, we present a microfluidic microwell array device that enables the massive parallel analysis of the immunocyte's heterogeneity upon its interaction pairs with tumor cells at the single cell level. By precisely controlling the number and ratio of tumor cells and T cells, our technique can interrogate the dynamics of the CD8+ T cell and leukemia cell interaction inside 6400 microfluidic wells simultaneously. We have demonstrated that by investigating the interactions of T cell and tumor cell pairs at the single cell level using our microfluidic chip, details hidden in bulk investigations, such as heterogeneity in T cell killing capacity, time dependent killing dynamics, as well as drug treatment induced dynamic shifts, can be revealed. This method opens up avenues to investigate the efficacy of cancer immunotherapy and resistance at the single cell level and can explore our understanding of fundamental cancer immunity as well as determine cancer immunotherapy efficacy for personalized therapy.
Auxin binding protein 1 (ABP1) is not required for either auxin signaling or Arabidopsis development
Venue: Proceedings of the National Academy of Sciences
Year: 2015

The plant hormone auxin is a key regulator of plant growth. It has been hypothesized that some auxin responses are mediated by a candidate auxin receptor called auxin binding protein 1 (ABP1) Support for this hypothesis mainly comes from the analyses of Arabidopsis ABP1 knockdown lines generated by cellular immunization or antisense approaches. However, these approaches are subject to off target effects. As an alternative, we have recovered two new null alleles of abp1. Surprisingly, neither of the mutants exhibits defects in growth and development, or auxin response, indicating that ABP1 does not have a major role in these responses under normal growth conditions. These results require that the role of ABP1 in plant growth and auxin response be reexamined. Auxin binding protein 1 (ABP1) has been studied for decades. It has been suggested that ABP1 functions as an auxin receptor and has an essential role in many developmental processes. Here we present our unexpected findings that ABP1 is neither required for auxin signaling nor necessary for plant development under normal growth conditions. We used our ribozyme based CRISPR technology to generate an Arabidopsis abp1 mutant that contains a 5 bp deletion in the first exon of ABP1, which resulted in a frameshift and introduction of early stop codons. We also identified a T DNA insertion abp1 allele that harbors a T DNA insertion located 27 bp downstream of the ATG start codon in the first exon. We show that the two new abp1 mutants are null alleles. Surprisingly, our new abp1 mutant plants do not display any obvious developmental defects. In fact, the mutant plants are indistinguishable from wild type plants at every developmental stage analyzed. Furthermore, the abp1 plants are not resistant to exogenous auxin. At the molecular level, we find that the induction of known auxin regulated genes is similar in both wild type and abp1 plants in response to auxin treatments. We conclude that ABP1 is not a key component in auxin signaling or Arabidopsis development.
Neutral Face Game Character Auto Creation via PokerFace GAN
Venue: ACM Multimedia
Year: 2020

Game character customization is one of the core features of many recent Role Playing Games (RPGs) where players can edit the appearance of their in game characters with their preferences. This paper studies the problem of automatically creating in game characters with a single photo. In recent literature on this topic, neural networks are introduced to make game engine differentiable and the self supervised learning is used to predict facial customization parameters. However, in previous methods, the expression parameters and facial identity parameters are highly coupled with each other, making it difficult to model the intrinsic facial features of the character. Besides, the neural network based renderer used in previous methods is also difficult to be extended to multi view rendering cases. In this paper, considering the above problems, we propose a novel method named "PokerFace GAN" for neutral face game character auto creation. We first build a differentiable character renderer which is more flexible than the previous methods in multi view rendering cases. We then take advantage of the adversarial training to effectively disentangle the expression parameters from the identity parameters and thus generate player preferred neutral face (expression less) characters. Since all components of our method are differentiable, our method can be easily trained under a multi task self supervised learning paradigm. Experiment results show that our method can generate vivid neutral face game characters that are highly similar to the input photos. The effectiveness of our method is verified by comparison results and ablation studies.