nils-herrmann/clean_scirepeval huggingface dataset:
Activity Detection with Latent Sub-event Hierarchy Learning

In this paper, we introduce a new convolutional layer named the Temporal Gaussian Mixture (TGM) layer and present how it can be used to efficiently capture temporal structure in continuous activity videos. Our layer is designed to allow the model to learn a latent hierarchy of sub-event intervals. Our approach is fully differentiable while relying on a significantly less number of parameters, enabling its end-to-end training with standard backpropagation. We present our convolutional video models with multiple TGM layers for activity detection. Our experiments on multiple datasets including Charades and MultiTHUMOS confirm the benefit of our TGM layers, illustrating that it outperforms other models and temporal convolutions.
Implications of the ‘Energide’ concept for communication and information handling in the central nervous system

Recently a revision of the cell theory has been proposed, which has several implications both for physiology and pathology. This revision is founded on adapting the old Julius von Sach’s proposal (1892) of the Energide as the fundamental universal unit of eukaryotic life. This view maintains that, in most instances, the living unit is the symbiotic assemblage of the cell periphery complex organized around the plasma membrane, some peripheral semi-autonomous cytosol organelles (as mitochondria and plastids, which may be or not be present), and of the Energide (formed by the nucleus, microtubules, and other satellite structures). A fundamental aspect is the proposal that the Energide plays a pivotal and organizing role of the entire symbiotic assemblage . The present paper discusses how the Energide paradigm implies a revision of the concept of the internal milieu. As a matter of fact, the Energide interacts with the cytoplasm that, in turn, interacts with the interstitial fluid, and hence with the medium that has been, classically, known as the internal milieu. Some implications of this aspect have been also presented with the help of a computational model in a mathematical Appendix 2 to the paper. Finally, relevances of the Energide concept for the information handling in the central nervous system are discussed especially in relation to the inter-Energide exchange of information.
Porphyromonas gingivalis: An Overview of Periodontopathic Pathogen below the Gum Line

Periodontal disease represents a group of oral inflammatory infections initiated by oral pathogens which exist as a complex biofilms on the tooth surface and cause destruction to tooth supporting tissues. The severity of this disease ranges from mild and reversible inflammation of the gingiva (gingivitis) to chronic destruction of connective tissues, the formation of periodontal pocket and ultimately result in loss of teeth. While human subgingival plaque harbors more than 500 bacterial species, considerable research has shown that Porphyromonas gingivalis, a Gram-negative anaerobic bacterium, is the major etiologic agent which contributes to chronic periodontitis. This black-pigmented bacterium produces a myriad of virulence factors that cause destruction to periodontal tissues either directly or indirectly by modulating the host inflammatory response. Here, this review provides an overview of P. gingivalis and how its virulence factors contribute to the pathogenesis with other microbiome consortium in oral cavity.
A minutia-based partial fingerprint recognition system

Matching incomplete or partial fingerprints continues to be an important challenge today, despite the advances made in fingerprint identification techniques. While the introduction of compact silicon chip-based sensors that capture only part of the fingerprint has made this problem important from a commercial perspective, there is also considerable interest in processing partial and latent fingerprints obtained at crime scenes. When the partial print does not include structures such as core and delta, common matching methods based on alignment of singular structures fail. We present an approach that uses localized secondary features derived from relative minutiae information. A flow network-based matching technique is introduced to obtain one-to-one correspondence of secondary features. Our method balances the tradeoffs between maximizing the number of matches and minimizing total feature distance between query and reference fingerprints. A two-hidden-layer fully connected neural network is trained to generate the final similarity score based on minutiae matched in the overlapping areas. Since the minutia-based fingerprint representation is an ANSI-NIST standard [American National Standards Institute, New York, 1993], our approach has the advantage of being directly applicable to existing databases. We present results of testing on FVC2002’s DB1 and DB2 databases.
Evaluating the level of evidence of qualitative research.

Guidelines for evaluating the levels of evidence based on quantitative research are well established. However, the same cannot be said for the evaluation of qualitative research. This article discusses a process members of an evidence-based clinical practice guideline development team with the Association of Women's Health, Obstetric and Neonatal Nurses used to create a scoring system to determine the strength of qualitative research evidence. A brief history of evidence-based clinical practice guideline development is provided, followed by discussion of the development of the Nursing Management of the Second Stage of Labor evidence-based clinical practice guideline. The development of the qualitative scoring system is explicated, and implications for nursing are proposed.
Elimination of Gate Leakage in GaN FETs by Placing Oxide Spacers on the Mesa Sidewalls

This letter reports the fabrication of a GaN heterostructure field-effect transistor with oxide spacer placed on the mesa sidewalls. The presence of an oxide spacer effectively eliminates the gate leakage current that occurs at the channel edge, where the gate metal is in contact with the 2-D electron gas edge on the mesa sidewall. From the two-terminal gate leakage current measurements, the leakage current was found to be several nA at VG=-12 V and at VG=-450 V. The benefits of the proposed spacer scheme include the patterning of the metal electrodes by plasma etching and a lower manufacturing cost.
Protecting Military Avionics Platforms from Attacks on MIL-STD-1553 Communication Bus

MIL-STD-1553 is a military standard that defines the physical and logical layers, and a command/response time division multiplexing of a communication bus used in military and aerospace avionic platforms for more than 40 years. As a legacy platform, MIL-STD-1553 was designed for high level of fault tolerance while less attention was taken with regard to security. Recent studies already addressed the impact of successful cyber attacks on aerospace vehicles that are implementing MIL-STD-1553. In this study we present a security analysis of MIL-STD-1553. In addition, we present a method for anomaly detection in MIL-STD-1553 communication bus and its performance in the presence of several attack scenarios implemented in a testbed, as well as results on real system data. Moreover, we propose a general approach towards an intrusion detection system (IDS) for a MIL-STD-1553 communication bus.
Animal models for bipolar disorder: from bedside to the cage

Bipolar disorder is characterized by recurrent manic and depressive episodes. Patients suffering from this disorder experience dramatic mood swings with a wide variety of typical behavioral facets, affecting overall activity, energy, sexual behavior, sense of self, self-esteem, circadian rhythm, cognition, and increased risk for suicide. Effective treatment options are limited and diagnosis can be complicated. To overcome these obstacles, a better understanding of the neurobiology underlying bipolar disorder is needed. Animal models can be useful tools in understanding brain mechanisms associated with certain behavior. The following review discusses several pathological aspects of humans suffering from bipolar disorder and compares these findings with insights obtained from several animal models mimicking diverse facets of its symptomatology. Various sections of the review concentrate on specific topics that are relevant in human patients, namely circadian rhythms, neurotransmitters, focusing on the dopaminergic system, stressful environment, and the immune system. We then explain how these areas have been manipulated to create animal models for the disorder. Even though several approaches have been conducted, there is still a lack of adequate animal models for bipolar disorder. Specifically, most animal models mimic only mania or depression and only a few include the cyclical nature of the human condition. Future studies could therefore focus on modeling both episodes in the same animal model to also have the possibility to investigate the switch from mania-like behavior to depressive-like behavior and vice versa. The use of viral tools and a focus on circadian rhythms and the immune system might make the creation of such animal models possible.
Detection of purple fringing aberration patterns and its application to forensic analysis of spliced images

Morphing, fusion and stitching of digital photographs from multiple sources is a common problem in the recent era. While images may depict visual normalcy despite a splicing operation, there are domains in which a consistency or an anomaly check can be performed to detect a covert digital stitching process. Most digital and low-end mobile cameras have certain intrinsic sensor aberrations such as purple fringing (PF), seen in image regions where there are contrast variations and shadowing. This paper proposes an approach based on Fuzzy clustering to first identify regions which contain Purple Fringing and is then used as a forensic tool to detect splicing operations. The accuracy of the Fuzzy clustering approach is comparable with the state-of-the-art PF detection methods and has been shown to penetrate standard interpolation and stitching operations performed using ADOBE PHOTOSHOP.
Multi-content GAN for Few-Shot Font Style Transfer

In this work, we focus on the challenge of taking partial observations of highly-stylized text and generalizing the observations to generate unobserved glyphs in the ornamented typeface. To generate a set of multi-content images following a consistent style from very few examples, we propose an end-to-end stacked conditional GAN model considering content along channels and style along network layers. Our proposed network transfers the style of given glyphs to the contents of unseen ones, capturing highly stylized fonts found in the real-world such as those on movie posters or infographics. We seek to transfer both the typographic stylization (ex. serifs and ears) as well as the textual stylization (ex. color gradients and effects.) We base our experiments on our collected data set including 10,000 fonts with different styles and demonstrate effective generalization from a very small number of observed glyphs.
Chaos in Random Dynamical Systems

In the investigations of chaos in dynamical systems a major role is played by symbolic dynamics, i.e. the description of the system by a shift on a symbol space via conjugation. We examine whether any kind of noise can strengthen the stochastic behaviour of chaotic systems dramatically and what the consequences for the symbolic description are. This leads to the introduction of random subshifts of nite type which are appropriate for the description of quite general dynamical systems evolving under the innuence of noise and showing internal stochastic features. We investigate some of the ergodic and stochastic properties of these shifts and show situations when they behave dynamically like the common shifts. In particular we want to present examples where such random shift systems appear as symbolic descriptions.
Partial differential equation-based approach for removal of chromatic aberration with local characteristics

bstract. We propose a chromatic aberration (CA) reduction techique that removes artifacts caused by lateral CA and longitudinal A, simultaneously. In general, most visible CA-related artifacts apear locally in the neighborhoods of strong edges. Because these rtifacts usually have local characteristics, they cannot be removed ell by regular global warping methods. Therefore, we designed a onlinear partial differential equation (PDE) in which the local charcteristics of the CA are taken into account. The proposed algorithm stimates the regions with apparent CA artifacts and the ratios of the agnitudes between the color channels. Using this information, the roposed PDE matches the gradients of the edges in the red and lue channels to the gradient in the green channel, which results in n alignment of the positions of the edges while simultaneously perorming a deblurring process on the edges. Experimental results how that the proposed method can effectively remove even signifiant CA artifacts, such as purple fringing as identified by the image ensor. The experimental results show that the proposed algorithm chieves better performance than existing algorithms.
Eating Habits and Dietary Intake: Is Adherence to Dietary Guidelines Associated with Importance of Healthy Eating among Undergraduate University Students in Finland?

Poor eating habits among young adults are a public health concern. This survey examined the eating habits of undergraduate university students in Finland. We assessed students' dietary intake of a variety of food groups, their adherence to international dietary guidelines (whole sample and by gender), and the associations between importance of eating healthy and dietary guidelines adherence (whole sample and by gender).



During the 2013-2014 academic year, 1,189 undergraduate students enrolled at the University of Turku in southwestern Finland completed an online self-administered questionnaire. Students reported their eating habits of 12 food groups, the number of daily servings of fruits/vegetables they consume and how important it is for them to eat healthy. For dietary adherence recommendations, we employed WHO guidelines. Chi-square statistic tested the differences in dietary guidelines adherence between males and females and also the associations between the gradients of importance of healthy eating and the self reported eating habits for each of the food groups, for the whole sample and by gender.



We observed high levels of dietary adherence (>70%) for most of the 'unhealthy food' items (cake/cookies, snacks, fast food/canned food, and lemonade/soft drinks), and moderate adherence for most of the 'healthy food' items (>50%) (dairy/dairy products, fruit/vegetables servings/day, fresh fruit, salads/raw vegetables and cereal/cereal products). Fish/seafood, meat/sausage products and cooked vegetables had levels <50% for adherence to the guidelines. Women had better adherence for meat/sausage products, fast food/canned food and for most 'healthy food' items (p≤0.001), whereas men had better adherence for sweets (difference=12.8%, p≤0.001), lemonade/soft drinks (difference=16.7%, p≤0.001) and fish/seafood (difference=6.6%, p=0.040) compared to women. Most students considered important to eat healthy (78.8%). The importance of eating healthy was significantly associated with adherence for all food groups besides sweets and cake/cookies. These associations remained significant for women but some of them not for men (cereal/cereal products, snacks and sweets).



The results suggest high adherence to the guidelines mainly for 'unhealthy food' groups, and moderate adherence for healthier food groups. There was also accordance between regarding eating healthy as important and actually eating healthy. However, there are improvements to be considered for specific food groups, as well as gender differences when implementing public health strategies related to food intake.
ESTABLISHING DOSE REFERENCE LEVEL FOR COMPUTED TOMOGRAPHY ( CT ) EXAMINATIONS IN MALAYSIA

This study is conducted with the collaboration of the Malaysian Atomic Energy Licensing Board (AELB) in order to establish dose reference level (DRL) for computed tomography (CT) examinations in Malaysia. 426 examinations for standard adult patients and 26 examinations for paediatric patients comprising different types of CT examinations were collected from 33 out of 109 (30.3%) hospitals that have CT scanner in Malaysia. Measurements of Computed Tomography Dose Index in air (CTDIair) were done at every CT scanner in the hospitals that were involved in this study to investigate the scanner-specific values comparable to the data published by the ImPACT. Effective doses for all CT examinations were calculated using ImPACT Dosimetry Calculator for both ImPACT CTDIair and measured CTDIair values as a comparison. This study found that 4% to 22% of deviations between both values and the deviations represent the dose influence factors contributed by the CT machines. Every protocol used at certain CT examinations were analysed and it was found that tube potential (kVp) was not the main contribution for effective doses deviation. Other scanning parameters such as tube current – time product (mAs), scan length and nonstandardisation in some of the procedures were significant contributors to the effective dose deviations in most of the CT examinations. Effective doses calculated using ImPACT CTDIair were used to compare with other studies to provide an overview of CT practice in Malaysia. Effective doses for examinations of routine head, routine chest and pelvis are within the same range with studies conducted for the European guidelines, the UK and Taiwan. For the routine abdomen examination, the effective dose is still within the range compared to the studies for European guidelines and Taiwan, but 55.1% higher than the value from the study conducted in the UK. Lastly, this study also provided the third quartile values of effective doses for every CT
Waking and dreaming: Related but structurally independent. Dream reports of congenitally paraplegic and deaf-mute persons

Models of dream analysis either assume a continuum of waking and dreaming or the existence of two dissociated realities. Both approaches rely on different methodology. Whereas continuity models are based on content analysis, discontinuity models use a structural approach. In our study, we applied both methods to test specific hypotheses about continuity or discontinuity. We contrasted dream reports of congenitally deaf-mute and congenitally paraplegic individuals with those of non-handicapped controls. Continuity theory would predict that either the deficit itself or compensatory experiences would surface in the dream narrative. We found that dream form and content of sensorially limited persons was indifferent from those of non-handicapped controls. Surprisingly, perceptual representations, even of modalities not experienced during waking, were quite common in the dream reports of our handicapped subjects. Results are discussed with respect to feedforward mechanisms and protoconsciousness theory of dreaming.
Association of Sprint Performance With Ground Reaction Forces During Acceleration and Maximal Speed Phases in a Single Sprint.

We aimed to clarify the mechanical determinants of sprinting performance during acceleration and maximal speed phases of a single sprint, using ground reaction forces (GRFs). While 18 male athletes performed a 60-m sprint, GRF was measured at every step over a 50-m distance from the start. Variables during the entire acceleration phase were approximated with a fourth-order polynomial. Subsequently, accelerations at 55%, 65%, 75%, 85%, and 95% of maximal speed, and running speed during the maximal speed phase were determined as sprinting performance variables. Ground reaction impulses and mean GRFs during the acceleration and maximal speed phases were selected as independent variables. Stepwise multiple regression analysis selected propulsive and braking impulses as contributors to acceleration at 55%-95% (β > 0.72) and 75%-95% (β > 0.18), respectively, of maximal speed. Moreover, mean vertical force was a contributor to maximal running speed (β = 0.48). The current results demonstrate that exerting a large propulsive force during the entire acceleration phase, suppressing braking force when approaching maximal speed, and producing a large vertical force during the maximal speed phase are essential for achieving greater acceleration and maintaining higher maximal speed, respectively.
Animated Words Clouds to View and Extract Knowledge from Textual Information

The presentation of information is a very important part of the comprehension of the whole. Therefore, the chosen visualization technique should be compatible with the content to be presented. An easy and fast visualization of the subjects developed by a research group, during certain periods, requires a dynamic visualization technique such as the Animated Word Cloud. With this technique, we were able to use the titles of bibliographic publications of researchers to present, in a clear and straightforward manner, information that is not easily evident just by reading its title. The synchronization of the videos generated from the Animated Word Clouds allows a deeper analysis, a quick and intuitive observation, and the perception of information presented simultaneously.
DP2PN2Solver: A flexible dynamic programming solver software tool

Dynamic programming (DP) is a very general optimization technique, which can be applied to numerous decision problems that typically require a sequence of decisions to be made. The solver software DP2PN2Solver presented in this paper is a general, flexible, and expandable software tool that solves DP problems. It consists of modules on two levels. A level one module takes the specification of a discrete DP problem instance as input and produces an intermediate Petri net (PN) representation called Bellman net (Lew, 2002; Lew, Mauch, 2003, 2004) as output — a middle layer, which concisely captures all the essential elements of a DP problem in a standardized and mathematically precise fashion. The optimal solution for the problem instance is computed by an “executable” code (e.g. Java, Spreadsheet, etc.) derived by a level two module from the Bellman net representation. DP2PN2Solver’s unique potential lies in its Bellman net representation. In theory, a PN’s intrinsic concurrency allows to distribute the computational load encountered when solving a single DP problem instance to several computational units.
Grammar Induction with Neural Language Models: An Unusual Replication

A substantial thread of recent work on latent tree learning has attempted to develop neural network models with parse-valued latent variables and train them on non-parsing tasks, in the hope of having them discover interpretable tree structure. In a recent paper, Shen et al. (2018) introduce such a model and report nearstate-of-the-art results on the target task of language modeling, and the first strong latent tree learning result on constituency parsing. In an attempt to reproduce these results, we discover issues that make the original results hard to trust, including tuning and even training on what is effectively the test set. Here, we attempt to reproduce these results in a fair experiment and to extend them to two new datasets. We find that the results of this work are robust: All variants of the model under study outperform all latent tree learning baselines, and perform competitively with symbolic grammar induction systems. We find that this model represents the first empirical success for latent tree learning, and that neural network language modeling warrants further study as a setting for grammar induction.