nils-herrmann/clean_scirepeval huggingface dataset:
Efficient physically-based shadow algorithms

Author Samuli Laine Title Efficient Physically-Based Shadow Algorithms This research focuses on developing efficient algorithms for computing shadows in computer-generated images. A distinctive feature of the shadow algorithms presented in this thesis is that they produce correct, physicallybased results, instead of giving approximations whose quality is often hard to ensure or evaluate. Light sources that are modeled as points without any spatial extent produce hard shadows with sharp boundaries. Shadow mapping is a traditional method for rendering such shadows. A shadow map is a depth buffer computed from the scene, using a point light source as the viewpoint. The finite resolution of the shadow map requires that its contents are resampled when determining the shadows on visible surfaces. This causes various artifacts such as incorrect self-shadowing and jagged shadow boundaries. A novel method is presented that avoids the resampling step, and provides exact shadows for every point visible in the image. The shadow volume algorithm is another commonly used algorithm for real-time rendering of hard shadows. This algorithm gives exact results and does not suffer from any resampling problems, but it tends to consume a lot of fillrate, which leads to performance problems. This thesis presents a new technique for locally choosing between two previous shadow volume algorithms with different performance characteristics. A simple criterion for making the local choices is shown to yield better performance than using either of the algorithms alone. Light sources with nonzero spatial extent give rise to soft shadows with smooth boundaries. A novel method is presented that transposes the classical processing order for soft shadow computation in offline rendering. Instead of casting shadow rays, the algorithm first conceptually collects every ray that would need to be cast, and then processes the shadow-casting primitives one by one, hierarchically finding the rays that are blocked. Another new soft shadow algorithm takes a different point of view into computing the shadows. Only the silhouettes of the shadow casters are used for determining the shadows, and an unintrusive execution model makes the algorithm practical for production use in offline rendering. The proposed techniques accelerate the computing of physically-based shadows in real-time and offline rendering. These improvements make it possible to use correct, physically-based shadows in a broad range of scenes that previous methods cannot handle efficiently enough. UDC 004.925, 004.383.5
How digital are we ? Maturity models for the assessment of a company ’ s status in the digital transformation

In the context of an ongoing digital transformation, companies across all industries are confronted with the challenge to exploit IT-induced business opportunities and to simultaneously avert IT-induced business risks. Due to this development, questions about a company’s overall status with regard to its digital transformation become more and more relevant. In recent years, an unclear number of maturity models was established in order to address these kind of questions by assessing a company’s digital maturity. Purpose of this Report is to show the large range of digital maturity models and to evaluate overall potential for approximating a company’s digital transformation status.
Motor Development and Physical Activity: A Longitudinal Discordant Twin-Pair Study.

Previous longitudinal research suggests that motor proficiency in early life predicts physical activity in adulthood. Familial effects including genetic and environmental factors could explain the association, but no long-term follow-up studies have taken into account potential confounding by genetic and social family background. The present twin study investigated whether childhood motor skill development is associated with leisure-time physical activity levels in adulthood independent of family background.



Altogether, 1550 twin pairs from the FinnTwin12 study and 1752 twin pairs from the FinnTwin16 study were included in the analysis. Childhood motor development was assessed by the parents' report of whether one of the co-twins had been ahead of the other in different indicators of motor skill development in childhood. Leisure-time physical activity (MET·h·d) was self-reported by the twins in young adulthood and adulthood. Statistical analyses included conditional and ordinary linear regression models within twin pairs.



Using all activity-discordant twin pairs, the within-pair difference in a sum score of motor development in childhood predicted the within-pair difference in the leisure-time physical activity level in young adulthood (P < 0.001). Within specific motor development indicators, learning to stand unaided earlier in infancy predicted higher leisure-time MET values in young adulthood statistically significantly in both samples (FinnTwin12, P = 0.02; and FinnTwin16, P = 0.001) and also in the pooled data set of the FinnTwin12 and FinnTwin16 studies (P < 0.001). Having been more agile than the co-twin as a child predicted higher leisure-time MET values up to adulthood (P = 0.03).



More advanced childhood motor development is associated with higher leisure-time MET values in young adulthood at least partly independent of family background in both men and women.
Exploring the combination rules of D numbers from a perspective of conflict redistribution

Dempster-Shafer theory of evidence is widely applied to uncertainty modelling and knowledge reasoning because of its advantages in dealing with uncertain information. But some conditions or requirements, such as exclusiveness hypothesis and completeness constraint, limit the development and application of that theory to a large extend. To overcome the shortcomings and enhance its capability of representing the uncertainty, a novel model, called D numbers, has been proposed recently. However, many key issues, for example how to implement the combination of D numbers, remain unsolved. In the paper, we have explored the combination of D Numbers from a perspective of conflict redistribution, and propose two combination rules being suitable for different situations for the fusion of two D numbers. The proposed combination rules can reduce to the classical Dempster's rule in Dempster-Shafer theory under certain conditions. Numerical examples and discussion about the proposed rules are also given in the paper.
Tree quantization for large-scale similarity search and classification

We propose a new vector encoding scheme (tree quantization) that obtains lossy compact codes for high-dimensional vectors via tree-based dynamic programming. Similarly to several previous schemes such as product quantization, these codes correspond to codeword numbers within multiple codebooks. We propose an integer programming-based optimization that jointly recovers the coding tree structure and the codebooks by minimizing the compression error on a training dataset. In the experiments with diverse visual descriptors (SIFT, neural codes, Fisher vectors), tree quantization is shown to combine fast encoding and state-of-the-art accuracy in terms of the compression error, the retrieval performance, and the image classification error.
Millimeter-Wave Communications: Physical Channel Models, Design Considerations, Antenna Constructions, and Link-Budget

The millimeter wave (mmWave) frequency band spanning from 30 to 300 GHz constitutes a substantial portion of the unused frequency spectrum, which is an important resource for future wireless communication systems in order to fulfill the escalating capacity demand. Given the improvements in integrated components and enhanced power efficiency at high frequencies, wireless systems can operate in the mmWave frequency band. In this paper, we present a survey of the mmWave propagation characteristics, channel modeling, and design guidelines, such as system and antenna design considerations for mmWave, including the link budget of the network, which are essential for mmWave communication systems. We commence by introducing the main channel propagation characteristics of mmWaves followed by channel modeling and design guidelines. Then, we report on the main measurement and modeling campaigns conducted in order to understand the mmWave band’s properties and present the associated channel models. We survey the different channel models focusing on the channel models available for the 28, 38, 60, and 73 GHz frequency bands. Finally, we present the mmWave channel model and its challenges in the context of mmWave communication systems design.
SERS detection of arsenic in water: A review.

Arsenic (As) is one of the most toxic contaminants found in the environment. Development of novel detection methods for As species in water with the potential for field use has been an urgent need in recent years. In past decades, surface-enhanced Raman scattering (SERS) has gained a reputation as one of the most sensitive spectroscopic methods for chemical and biomolecular sensing. The SERS technique has emerged as an extremely promising solution for in-situ detection of arsenic species in the field, particularly when coupled with portable/handheld Raman spectrometers. In this article, the recent advances in SERS analysis of arsenic species in water media are reviewed, and the potential of this technique for fast screening and field testing of arsenic-contaminated environmental water samples is discussed. The problems that remain in the field are also discussed and an outlook for the future is featured at the end of the article.
Treatment of Alzheimer's disease: current and future therapeutic approaches.

The pathophysiology of Alzheimer's disease (AD) includes the deposition of amyloid beta protein (Abeta) and the ensuing initiation of a variety of secondary processes, including tau hyperphosphorylation, excitotoxicity, oxidation, and inflammation. Nerve cell loss in structures responsible for manufacturing neurotransmitters results in a variety of neurochemical deficits. Current therapeutic approaches to the treatment of AD include cholinesterase inhibitors for mild to moderate disease, memantine for moderate to severe disease, and vitamin E or selegiline. Reduction of Abeta generation or aggregation, enhancement of Abeta removal, interruption of tau hyperphosphorylation, and the use of more efficacious antioxidant or anti-inflammatory agents represent promising therapeutic strategies currently being investigated. Improved methodologies for clinical trial design and analysis and the development of biological markers may hasten the identification of effective treatments for AD.
New insights into the progression of aortic stenosis: implications for secondary prevention.

The risk factors affecting aortic stenosis (AS) progression are not clearly defined. Insights into this may allow for its secondary prevention.



We investigated predictors of AS progression in 170 consecutive patients with AS who had paired echocardiograms > or =3 months (23+/-11) apart. Various clinical, echocardiographic, and biochemical variables were related to the change in aortic valve area (AVA). The annual rate of reduction in AVA was 0.10+/-0.27 cm(2) or 7+/-18% per year. The reduction in AVA per year was significantly related to initial AVA (r = 0.46, P<0.0001), the mean aortic valve gradient (r = 0.27, P = 0.04), left ventricular (LV) outflow tract velocity (r = 0.26, P = 0.001), and LV end-diastolic diameter (r = 0.20, P = 0.04) and marginally to serum creatinine level (r = 0.15, P = 0.08). Patients with a rate of reduction in AVA faster than the mean had higher serum creatinine (P = 0.04) and calcium (P = 0.08) levels. Those with a serum cholesterol level >200 mg/dL had a rate of AVA reduction roughly twice that of those with a lower cholesterol level (P = 0.04). Stepwise multiple regression analysis identified initial AVA, current smoking, and serum calcium level as the independent predictors of amount of AVA reduction per year.



Absolute and percentage reduction in AVA per year in those with AS is greater in those with milder degrees of stenosis and is accelerated in the presence of smoking, hypercholesterolemia, and elevated serum creatinine and calcium levels. These findings may have important implications in gaining further insights into the mechanism of AS progression and in formulating strategies to retard this process.
A tree branch instead of a ligature: an unusual accidental hanging.

A unique case of accidental hanging due to compression of the neck of an adult by the branches of a coffee tree is reported. The decedent was a 42-year-old male who was found dead in a semi prone position on a slope. His neck was lodged in a wedge formed by two branches of a coffee tree, with his legs angled downwards on the slope. Autopsy revealed two friction abrasions located horizontally on either side of the front of the neck, just above the larynx. The findings were compatible with compression of the neck by the branches of the tree, with the body weight of the decedent contributing to compression. Subsequent complete autopsy examination confirmed the cause of death as hanging. Following an inquest the death was ruled to be accidental.
- 9359 ( Volume-3 , Issue-8 ) PCB Defect Detection and Classification Using Image Processing

Printed circuit boards are by far the most common method of assembling modern electronic circuits. During the manufacturing of PCB many defects are introduced which are harmful to precision circuit performance. A variety of ways has been established to detect the defects found on PCB, but it is also necessary to classify these defects so that the source of these defects can be identified. This study proposes an algorithm to group all 14 defects found on PCB into 5 Groups .the proposed algorithm involves MATLAB image processing operations ,such as image subtraction, image addition, logical XOR, Flood fill, Opening ,erosion.  PCB, Defects, Image processing, MATLAB,
A new contactless fault diagnosis approach for pantograph-catenary system

Railway transport is one of the most important mass transportation media in the worldwide. With the development of trains speed, safety and comfort levels of railways is getting more importance day by day. Besides high level of security requirement, detection of anomaly for rail and road shall be early identified for decreasing operation and maintenance expenditures. The pantograph-catenary system has an important role for collecting the current in electrical railways. The problem occurred in this system will affect the current collection performance of electrified trains. In this paper, a new image processing based technique is proposed to detect the arcing faults occurred between catenary and pantograph contact. The proposed method takes one frame from the digital camera and then the edge detection algorithm extracts the edges of pantograph. The arcing between contact wire and pantograph is detected by examining the position of contact wire of pantograph's edge.
C OG C OMP NLP : Your Swiss Army Knife for NLP

Implementing a Natural Language Processing (NLP) system requires considerable engineering effort: creating data-structures to represent language constructs; reading corpora annotations into these data-structures; applying off-the-shelf NLP tools to augment the text representation; extracting features and training machine learning components; conducting experiments and computing performance statistics; and creating the end-user application that integrates the implemented components. While there are several widely used NLP libraries, each provides only partial coverage of these various tasks. We present our library COGCOMPNLP which simplifies the process of design and development of NLP applications by providing modules to address different challenges: we provide a corpus-reader module that supports popular corpora in the NLP community, a module for various low-level data-structures and operations (such as search over text), a module for feature extraction, and an extensive suite of annotation modules for a wide range of semantic and syntactic tasks. These annotation modules are all integrated in a single system, PIPELINE, which allows users to easily use the annotators with simple direct calls using any JVM-based language, or over a network. The sister project COGCOMPNLPY enables users to access the annotators with a Python interface. We give a detailed account of our system’s structure and usage, and where possible, compare it with other established NLP frameworks. We report on the performance, including time and memory statistics, of each component on a selection of well-established datasets. Our system is publicly available for research use and external contributions, at: http://github.com/CogComp/cogcomp-nlp.
Microneedle-based drug delivery systems: microfabrication, drug delivery, and safety.

Many promising therapeutic agents are limited by their inability to reach the systemic circulation, due to the excellent barrier properties of biological membranes, such as the stratum corneum (SC) of the skin or the sclera/cornea of the eye and others. The outermost layer of the skin, the SC, is the principal barrier to topically-applied medications. The intact SC thus provides the main barrier to exogenous substances, including drugs. Only drugs with very specific physicochemical properties (molecular weight < 500 Da, adequate lipophilicity, and low melting point) can be successfully administered transdermally. Transdermal delivery of hydrophilic drugs and macromolecular agents of interest, including peptides, DNA, and small interfering RNA is problematic. Therefore, facilitation of drug penetration through the SC may involve by-pass or reversible disruption of SC molecular architecture. Microneedles (MNs), when used to puncture skin, will by-pass the SC and create transient aqueous transport pathways of micron dimensions and enhance the transdermal permeability. These micropores are orders of magnitude larger than molecular dimensions, and, therefore, should readily permit the transport of hydrophilic macromolecules. Various strategies have been employed by many research groups and pharmaceutical companies worldwide, for the fabrication of MNs. This review details various types of MNs, fabrication methods and, importantly, investigations of clinical safety of MN.
FacetAtlas: Multifaceted Visualization for Rich Text Corpora

Documents in rich text corpora usually contain multiple facets of information. For example, an article about a specific disease often consists of different facets such as symptom, treatment, cause, diagnosis, prognosis, and prevention. Thus, documents may have different relations based on different facets. Powerful search tools have been developed to help users locate lists of individual documents that are most related to specific keywords. However, there is a lack of effective analysis tools that reveal the multifaceted relations of documents within or cross the document clusters. In this paper, we present FacetAtlas, a multifaceted visualization technique for visually analyzing rich text corpora. FacetAtlas combines search technology with advanced visual analytical tools to convey both global and local patterns simultaneously. We describe several unique aspects of FacetAtlas, including (1) node cliques and multifaceted edges, (2) an optimized density map, and (3) automated opacity pattern enhancement for highlighting visual patterns, (4) interactive context switch between facets. In addition, we demonstrate the power of FacetAtlas through a case study that targets patient education in the health care domain. Our evaluation shows the benefits of this work, especially in support of complex multifaceted data analysis.
FANET Based Flights Monitoring Simulation System Over Cloud

As mounting population and need of advance commutes systems, available vehicular ad hoc networks (VANET) systems will not suffice the communication complex issues between vehicles on land, water and air. In order to meet ever growing challenges, VANET cloud computing techniques start contributing with its supple state line less storage, high end virtual techniques and logical schema connectivity to make commute rich, safe and pleasure experience to users. In this paper, we proposed an architectural model for flight monitoring simulation, which optimizes the scheduling of flights in the most prominent manner by centralizing all resources at single cloud which optimizes the time management of effective communication among resources. This model will be an immense resource not only for commercial flights but also for air force navigation systems. VANET existing systems were designed for vehicular networks while our proposed solution flying ad hoc networks (FANET) or Flights Air Networks adapts VANET approach on high speed air traffic, FANET may use electromagnetic waves for data transfer between flights as electromagnetic waves speed is much higher than flights speeds, it may ensure timely communication between flights and other communicating sources. V. Tiwari (&) K. Sharma B.K. Chaurasia Department of CSE, ITM University Gwalior, Gwalior, India e-mail: getvipultiwari@gmail.com K. Sharma e-mail: kapil.rjit@gmail.com B.K. Chaurasia e-mail: bkchaurasia.itm@gmail.com
Estradiol and the developing brain.

Estradiol is the most potent and ubiquitous member of a class of steroid hormones called estrogens. Fetuses and newborns are exposed to estradiol derived from their mother, their own gonads, and synthesized locally in their brains. Receptors for estradiol are nuclear transcription factors that regulate gene expression but also have actions at the membrane, including activation of signal transduction pathways. The developing brain expresses high levels of receptors for estradiol. The actions of estradiol on developing brain are generally permanent and range from establishment of sex differences to pervasive trophic and neuroprotective effects. Cellular end points mediated by estradiol include the following: 1) apoptosis, with estradiol preventing it in some regions but promoting it in others; 2) synaptogenesis, again estradiol promotes in some regions and inhibits in others; and 3) morphometry of neurons and astrocytes. Estradiol also impacts cellular physiology by modulating calcium handling, immediate-early-gene expression, and kinase activity. The specific mechanisms of estradiol action permanently impacting the brain are regionally specific and often involve neuronal/glial cross-talk. The introduction of endocrine disrupting compounds into the environment that mimic or alter the actions of estradiol has generated considerable concern, and the developing brain is a particularly sensitive target. Prostaglandins, glutamate, GABA, granulin, and focal adhesion kinase are among the signaling molecules co-opted by estradiol to differentiate male from female brains, but much remains to be learned. Only by understanding completely the mechanisms and impact of estradiol action on the developing brain can we also understand when these processes go awry.