nils-herrmann/clean_scirepeval huggingface dataset:
Measuring author research relatedness: A comparison of word-based, topic-based, and author cocitation approaches

Relationships between authors based on characteristics of published literature have been studied for decades. Author cocitation analysis using mapping techniques has been most frequently used to study how closely two authors are thought to be in intellectual space based on how members of the research community co-cite their works. Other approaches exist to study author relatedness based more directly on the text of their published works. In this study we present static and dynamic word-based approaches using vector space modeling, as well as a topic-based approach based on Latent Dirichlet Allocation for mapping author research relatedness. Vector space modeling is used to define an author space consisting of works by a given author. Outcomes for the two word-based approaches and a topic-based approach for 50 prolific authors in library and information science are compared with more traditional author cocitation analysis using multidimensional scaling and hierarchical cluster analysis. The two word-based approaches produced similar outcomes except where two authors were frequent co-authors for the majority of their articles. The topic-based approach produced the most distinctive map.
The Possibility of Altruism pdf -

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A Point-Cloud-Based Multiview Stereo Algorithm for Free-Viewpoint Video

This paper presents a robust multiview stereo (MVS) algorithm for free-viewpoint video. Our MVS scheme is totally point-cloud-based and consists of three stages: point cloud extraction, merging, and meshing. To guarantee reconstruction accuracy, point clouds are first extracted according to a stereo matching metric which is robust to noise, occlusion, and lack of texture. Visual hull information, frontier points, and implicit points are then detected and fused with point fidelity information in the merging and meshing steps. All aspects of our method are designed to counteract potential challenges in MVS data sets for accurate and complete model reconstruction. Experimental results demonstrate that our technique produces the most competitive performance among current algorithms under sparse viewpoint setups according to both static and motion MVS data sets.
Equivalent-accuracy accelerated neural-network training using analogue memory

Neural-network training can be slow and energy intensive, owing to the need to transfer the weight data for the network between conventional digital memory chips and processor chips. Analogue non-volatile memory can accelerate the neural-network training algorithm known as backpropagation by performing parallelized multiply–accumulate operations in the analogue domain at the location of the weight data. However, the classification accuracies of such in situ training using non-volatile-memory hardware have generally been less than those of software-based training, owing to insufficient dynamic range and excessive weight-update asymmetry. Here we demonstrate mixed hardware–software neural-network implementations that involve up to 204,900 synapses and that combine long-term storage in phase-change memory, near-linear updates of volatile capacitors and weight-data transfer with ‘polarity inversion’ to cancel out inherent device-to-device variations. We achieve generalization accuracies (on previously unseen data) equivalent to those of software-based training on various commonly used machine-learning test datasets (MNIST, MNIST-backrand, CIFAR-10 and CIFAR-100). The computational energy efficiency of 28,065 billion operations per second per watt and throughput per area of 3.6 trillion operations per second per square millimetre that we calculate for our implementation exceed those of today’s graphical processing units by two orders of magnitude. This work provides a path towards hardware accelerators that are both fast and energy efficient, particularly on fully connected neural-network layers. Analogue-memory-based neural-network training using non-volatile-memory hardware augmented by circuit simulations achieves the same accuracy as software-based training but with much improved energy efficiency and speed.
Defending the Co-Branding Benefits of Sponsorship B 2 B Partnerships : The Case of Ambush Marketing

As THE 2006 WINTER OLYMPICS fast approach, and as athletes work to attain their scientifically scheduled peak physical form, corporate sponsors are gearing up for a different battle. Having invested in the Games and tied their brand strategy to the Olympic theme, they must now guard jealously this positioning in the face of "ambushers"— direct competitors striving to catch an illicit ride on the Olympic wave by deceiving or confusing consumers into believing they too are official sponsors. Long regarded as merely one among a battery of available marketing communication tools, sponsorship is now a powerful vehicle used by major organizations the world over to build brand value. In the process, it has become the foundation of dynamic business-to-business (B2B) relationships built on the premise that the brand of the sponsor and that of the sport or event it is associated with can be both successfully and synergistically enhanced over time (Stipp and Schiavone, 1996). In short, sponsorship has become a strategic vehicle for co-branding partnerships (Cliffe and Motion, 2005) with evidence of great success: Adidas' strengthened association with World Cup soccer has been widely credited with significantly contributing to the brand's market share increases. from 2 percent to 5 percent, in just four years (Keller, 1999). However, while strategic partnerships are increasingly important tools of competitive strategies, they also present significant challenges, with research suggesting failure rates of close to 50 percent (Inkpen and Ross, 2001). For instance, despite the obvious advantages of sponsorship as a co-branding partnership, including the ability to set up exclusive agreements that are rare or impossible in other contexts, sponsorship suffers specific threats, not least as a result of efforts by ambush marketers. That sports marketing is now one of the biggest business games in town is not under dispute. Recent figures demonstrate the growth and significance of sponsorship budgets around the world. For example. Table 1 shows the price tags of various sports sponsorship agreements. Given the magnitude of these expenditures, that little exists in the way of guidance about how to secure and protect sponsorship value is perplexing. Moreover, given the strategic significance of the longterm co-branding efforts undertaken by both sponsors and sport or event properties, it is somewhat surprising that so little analysis has examined the impact of ambush marketing nor elaborated possible responses to such a threat.
RDF Data Management: A survey of RDBMS-Based Approaches

This paper surveys approaches and up-to-date information of RDF data management and then categorizes them into four main RDF storages. Then, the survey restricts the discussion to those methods that solve RDF data management using a RDBMS, since it gives better performance and query optimization as a result of the large quantity of work required to induce relational query efficiency and also the scalability of its storage comes into play, with respect to scalability and various characteristics of performance.
Estimation of the POD function and the LOD of a qualitative microbiological measurement method.

Qualitative microbiological measurement methods in which the measurement results are either 0 (microorganism not detected) or 1 (microorganism detected) are discussed. The performance of such a measurement method is described by its probability of detection as a function of the contamination (CFU/g or CFU/mL) of the test material, or by the LOD(p), i.e., the contamination that is detected (measurement result 1) with a specified probability p. A complementary log-log model was used to statistically estimate these performance characteristics. An intralaboratory experiment for the detection of Listeria monocytogenes in various food matrixes illustrates the method. The estimate of LOD50% is compared with the Spearman-Kaerber method.
Secure nearest neighbor revisited

In this paper, we investigate the secure nearest neighbor (SNN) problem, in which a client issues an encrypted query point E(q) to a cloud service provider and asks for an encrypted data point in E(D) (the encrypted database) that is closest to the query point, without allowing the server to learn the plaintexts of the data or the query (and its result). We show that efficient attacks exist for existing SNN methods [21], , even though they were claimed to be secure in standard security models (such as indistinguishability under chosen plaintext or ciphertext attacks). We also establish a relationship between the SNN problem and the order-preserving encryption (OPE) problem from the cryptography field [6], , and we show that SNN is at least as hard as OPE. Since it is impossible to construct secure OPE schemes in standard security models [6], , our results imply that one cannot expect to find the exact (encrypted) nearest neighbor based on only E(q) and E(D). Given this hardness result, we design new SNN methods by asking the server, given only E(q) and E(D), to return a relevant (encrypted) partition E(G) from E(D) (i.e., G ⊆ D), such that that E(G) is guaranteed to contain the answer for the SNN query. Our methods provide customizable tradeoff between efficiency and communication cost, and they are as secure as the encryption scheme E used to encrypt the query and the database, where E can be any well-established encryption schemes.
Anti-Makeup: Learning A Bi-Level Adversarial Network for Makeup-Invariant Face Verification

Makeup is widely used to improve facial attractiveness and is well accepted by the public. However, different makeup styles will result in significant facial appearance changes. It remains a challenging problem to match makeup and non-makeup face images. This paper proposes a learning from generation approach for makeup-invariant face verification by introducing a bi-level adversarial network (BLAN). To alleviate the negative effects from makeup, we first generate non-makeup images from makeup ones, and then use the synthesized nonmakeup images for further verification. Two adversarial networks in BLAN are integrated in an end-to-end deep network, with the one on pixel level for reconstructing appealing facial images and the other on feature level for preserving identity information. These two networks jointly reduce the sensing gap between makeup and non-makeup images. Moreover, we make the generator well constrained by incorporating multiple perceptual losses. Experimental results on three benchmark makeup face datasets demonstrate that our method achieves state-of-the-art verification accuracy across makeup status and can produce photo-realistic non-makeup
Iterative Residual Network for Deep Joint Image Demosaicking and Denoising

Modern digital cameras rely on sequential execution of separate image processing steps to produce realistic images. The first two steps are usually related to denoising and demosaicking where the former aims to reduce noise from the sensor and the latter converts a series of light intensity readings to color images. Modern approaches try to jointly solve these problems, i.e joint denoising-demosaicking which is an inherently ill-posed problem given that two-thirds of the intensity information are missing and the rest are perturbed by noise. While there are several machine learning systems that have been recently introduced to tackle this problem, in this work we propose a novel algorithm which is inspired by powerful classical image regularization methods, large-scale optimization and deep learning techniques. Consequently, our derived iterative neural network has a transparent and clear interpretation compared to other black-box data driven approaches. The extensive comparisons that we report demonstrate the superiority of our proposed network, which outperforms any previous approaches on both noisy and noise-free data across many different datasets using less training samples. This improvement in reconstruction quality is attributed to the principled way we design and train our network architecture, which as a result requires fewer trainable parameters than the current state-of-the-art solution.
Separation anxiety avoidance inventory-child and parent version: psychometric properties and clinical utility in a clinical and school sample.

The psychometric properties and clinical utility of the Separation Anxiety Avoidance Inventory, child and parent version (SAAI-C/P) were examined in two studies. The aim of the SAAI, a self- and parent-report measure, is to evaluate the avoidance relating to separation anxiety disorder (SAD) situations. In the first study, a school sample of 384 children and their parents (n = 279) participated. In the second study, 102 children with SAD and 35 children with other anxiety disorders (AD) were investigated. In addition, 93 parents of children with SAD, and 35 parents of children with other AD participated. A two-factor structure was confirmed by confirmatory factor analysis. The SAAI-C and SAAI-P demonstrated good internal consistency, test-retest reliability, as well as construct and discriminant validity. Furthermore, the SAAI was sensitive to treatment change. The parent-child agreement was substantial. Overall, these results provide support for the use of the SAAI-C/P version in clinical and research settings.
A new 3D model retrieval approach based on the elevation descriptor

The advances in 3D data acquisition techniques, graphics hardware, and 3D data modeling and visualizing techniques have led to the proliferation of 3D models. This has made the searching for specific 3D models a vital issue. Techniques for effective and efficient content-based retrieval of 3D models have therefore become an essential research topic. In this paper, a novel feature, called elevation descriptor, is proposed for 3D model retrieval. The elevation descriptor is invariant to translation and scaling of 3D models and it is robust for rotation. First, six elevations are obtained to describe the altitude information of a 3D model from six different views. Each elevation is represented by a gray-level image which is decomposed into several concentric circles. The elevation descriptor is obtained by taking the difference between the altitude sums of two successive concentric circles. An efficient similarity matching method is used to find the best match for an input model. Experimental results show that the proposed method is superior to other descriptors, including spherical harmonics, the MPEG-7 3D shape spectrum descriptor, and D2. 2006 Pattern Recognition Society.
Light Absorption and Energy Transfer in the Antenna Complexes of Photosynthetic Organisms.

The process of photosynthesis is initiated by the capture of sunlight by a network of light-absorbing molecules (chromophores), which are also responsible for the subsequent funneling of the excitation energy to the reaction centers. Through evolution, genetic drift, and speciation, photosynthetic organisms have discovered many solutions for light harvesting. In this review, we describe the underlying photophysical principles by which this energy is absorbed, as well as the mechanisms of electronic excitation energy transfer (EET). First, optical properties of the individual pigment chromophores present in light-harvesting antenna complexes are introduced, and then we examine the collective behavior of pigment-pigment and pigment-protein interactions. The description of energy transfer, in particular multichromophoric antenna structures, is shown to vary depending on the spatial and energetic landscape, which dictates the relative coupling strength between constituent pigment molecules. In the latter half of the article, we focus on the light-harvesting complexes of purple bacteria as a model to illustrate the present understanding of the synergetic effects leading to EET optimization of light-harvesting antenna systems while exploring the structure and function of the integral chromophores. We end this review with a brief overview of the energy-transfer dynamics and pathways in the light-harvesting antennas of various photosynthetic organisms.
VideoSET: Video Summary Evaluation through Text

In this paper we present VideoSET, a method for Video  Evaluation through Text that can evaluate how well a video summary is able to retain the semantic information contained in its original video. We observe that semantics is most easily expressed in words, and develop a text-based approach for the evaluation. Given a video summary, a text representation of the video summary is first generated, and an NLP-based metric is then used to measure its semantic distance to ground-truth text summaries written by humans. We show that our technique has higher agreement with human judgment than pixel-based distance metrics. We also release text annotations and ground-truth text summaries for a number of publicly available video datasets, for use by the computer vision community.
Origami based Mechanical Metamaterials

We describe mechanical metamaterials created by folding flat sheets in the tradition of origami, the art of paper folding, and study them in terms of their basic geometric and stiffness properties, as well as load bearing capability. A periodic Miura-ori pattern and a non-periodic Ron Resch pattern were studied. Unexceptional coexistence of positive and negative Poisson's ratio was reported for Miura-ori pattern, which are consistent with the interesting shear behavior and infinity bulk modulus of the same pattern. Unusually strong load bearing capability of the Ron Resch pattern was found and attributed to the unique way of folding. This work paves the way to the study of intriguing properties of origami structures as mechanical metamaterials.
Microbial and algal oils: Do they have a future for biodiesel or as commodity oils?

We review the prospects of using yeasts and microalgae as sources of cheap oils that could be used for biodiesel. We conclude that yeast oils, the cheapest of the oils producible by heterotrophic microorganisms, are too expensive to be viable alternatives to the major commodity plant oils. Algal oils are similarly unlikely to be economic; the cheapest form of cultivation is in open ponds which then requires a robust, fast-growing alga that can withstand adventitious predatory protozoa or contaminating bacteria and, at the same time, attain an oil content of at least 40% of the biomass. No such alga has yet been identified. However, we note that if the prices of the major plant oils and crude oil continue to rise in the future, as they have done over the past 12 months, then algal lipids might just become a realistic alternative within the next 10 to 15 years. Better prospects would, however, be to focus on algae as sources of polyunsaturated fatty acids.
Supramolecular systems chemistry.

The field of supramolecular chemistry focuses on the non-covalent interactions between molecules that give rise to molecular recognition and self-assembly processes. Since most non-covalent interactions are relatively weak and form and break without significant activation barriers, many supramolecular systems are under thermodynamic control. Hence, traditionally, supramolecular chemistry has focused predominantly on systems at equilibrium. However, more recently, self-assembly processes that are governed by kinetics, where the outcome of the assembly process is dictated by the assembly pathway rather than the free energy of the final assembled state, are becoming topical. Within the kinetic regime it is possible to distinguish between systems that reside in a kinetic trap and systems that are far from equilibrium and require a continuous supply of energy to maintain a stationary state. In particular, the latter systems have vast functional potential, as they allow, in principle, for more elaborate structural and functional diversity of self-assembled systems - indeed, life is a prime example of a far-from-equilibrium system. In this Review, we compare the different thermodynamic regimes using some selected examples and discuss some of the challenges that need to be addressed when developing new functional supramolecular systems.
Creating , Transporting , Cutting , and Merging Liquid Droplets by Electrowetting-Based Actuation for Digital Microfluidic Circuits

This paper reports the completion of four fundamental fluidic operations considered essential to build digital microfluidic circuits, which can be used for lab-on-a-chip or micro total analysis system ( TAS): 1) creating, 2) transporting, 3) cutting, and 4) merging liquid droplets, all by electrowetting, i.e., controlling the wetting property of the surface through electric potential. The surface used in this report is, more specifically, an electrode covered with dielectrics, hence, called electrowetting-on-dielectric (EWOD). All the fluidic movement is confined between two plates, which we call parallel-plate channel, rather than through closed channels or on open surfaces. While transporting and merging droplets are easily verified, we discover that there exists a design criterion for a given set of materials beyond which the droplet simply cannot be cut by EWOD mechanism. The condition for successful cutting is theoretically analyzed by examining the channel gap, the droplet size and the degree of contact angle change by electrowetting on dielectric (EWOD). A series of experiments is run and verifies the criterion. A smaller channel gap, a larger droplet size and a larger change in the contact angle enhance the necking of the droplet, helping the completion of the cutting process. Creating droplets from a pool of liquid is highly related to cutting, but much more challenging. Although droplets may be created by simply pulling liquid out of a reservoir, the location of cutting is sensitive to initial conditions and turns out unpredictable. This problem of an inconsistent cutting location is overcome by introducing side electrodes, which pull the liquid perpendicularly to the main fluid path before activating the cutting. All four operations are carried out in air environment at 25 Vdc applied voltage. [862]