Miracle-dz/UniFAR-FTUs huggingface dataset:
Distinct Molecular Features of Different Macroscopic Subtypes of Colorectal Neoplasms

BACKGROUND Colorectal adenoma develops into cancer with the accumulation of genetic and epigenetic changes. We studied the underlying molecular and clinicopathological features to better understand the heterogeneity of colorectal neoplasms (CRNs). METHODS We evaluated both genetic (mutations of KRAS, BRAF, TP53, and PIK3CA, and microsatellite instability [MSI]) and epigenetic (methylation status of nine genes or sequences, including the CpG island methylator phenotype [CIMP] markers) alterations in 158 CRNs including 56 polypoid neoplasms (PNs), 25 granular type laterally spreading tumors (LST-Gs), 48 non-granular type LSTs (LST-NGs), 19 depressed neoplasms (DNs) and 10 small flat-elevated neoplasms (S-FNs) on the basis of macroscopic appearance. RESULTS S-FNs showed few molecular changes except SFRP1 methylation. Significant differences in the frequency of KRAS mutations were observed among subtypes (68% for LST-Gs, 36% for PNs, 16% for DNs and 6% for LST-NGs) (P<0.001). By contrast, the frequency of TP53 mutation was higher in DNs than PNs or LST-Gs (32% vs. 5% or 0%, respectively) (P<0.007). We also observed significant differences in the frequency of CIMP between LST-Gs and LST-NGs or PNs (32% vs. 6% or 5%, respectively) (P<0.005). Moreover, the methylation level of LINE-1 was significantly lower in DNs or LST-Gs than in PNs (58.3% or 60.5% vs. 63.2%, P<0.05). PIK3CA mutations were detected only in LSTs. Finally, multivariate analyses showed that macroscopic morphologies were significantly associated with an increased risk of molecular changes (PN or LST-G for KRAS mutation, odds ratio [OR] 9.11; LST-NG or DN for TP53 mutation, OR 5.30; LST-G for PIK3CA mutation, OR 26.53; LST-G or DN for LINE-1 hypomethylation, OR 3.41). CONCLUSION We demonstrated that CRNs could be classified into five macroscopic subtypes according to clinicopathological and molecular differences, suggesting that different mechanisms are involved in the pathogenesis of colorectal tumorigenesis.
Inverterless high power interior permanent magnet automotive alternator

This paper describes a high power brushless interior permanent magnet (PM) automotive alternator which does not use an inverter. The “inverterless” alternator is designed with a high back-emf voltage and high reactance, and thus operates as a constant current source over much of its wide constant power operating speed range. In this configuration, a switched-mode rectifier is used to regulate the DC output voltage and current, which avoids the complexity and high cost of an inverter. The analysis of the modelling and performance of interior PM machines for this inverterless topology is described and experimental results are presented for a 6kW concept demonstrator machine showing an outstanding constant power speed range.
Edited by Lars Sjödahl, le.sjodahl@swipnet.se The contributions to this year’s Brunswik Newsletter cover a wide range of research topics from Clinical Judgement of Quality of Life to Cognitive Engineering and Improving Human–Automation Systems, just to mention some examples

The contributions to this year’s Brunswik Newsletter cover a wide range of research topics from Clinical Judgement of Quality of Life to Cognitive Engineering and Improving Human–Automation Systems, just to mention some examples. Ken Hammond looks back on the history of the Brunswik Society since it was organized 25 years ago in Boston and gives a compressed reminder of Brunswik’s 5 key-concepts, which are the cornerstones in his theoretical stand on organismenvironmental interaction. These concepts are so broadly defined that they, like open doors, still invite researchers to new contentand meaning-specifications.
Unsupervised Dependency Parsing: Let’s Use Supervised Parsers

We present a self-training approach to unsupervised dependency parsing that reuses existing supervised and unsupervised parsing algorithms. Our approach, called ‘iterated reranking’ (IR), starts with dependency trees generated by an unsupervised parser, and iteratively improves these trees using the richer probability models used in supervised parsing that are in turn trained on these trees. Our system achieves 1.8% accuracy higher than the stateof-the-part parser of Spitkovsky et al. (2013) on the WSJ corpus.
Detection of Anthropogenic Climate Change in the World's Oceans

Large-scale increases in the heat content of the world's oceans have been observed to occur over the last 45 years. The horizontal and temporal character of these changes has been closely replicated by the state-of-the-art Parallel Climate Model (PCM) forced by observed and estimated anthropogenic gases. Application of optimal detection methodology shows that the model-produced signals are indistinguishable from the observations at the 0.05 confidence level. Further, the chances of either the anthropogenic or observed signals being produced by the PCM as a result of natural, internal forcing alone are less than 5%. This suggests that the observed ocean heat-content changes are consistent with those expected from anthropogenic forcing, which broadens the basis for claims that an anthropogenic signal has been detected in the global climate system. Additionally, the requirement that modeled ocean heat uptakes match observations puts a strong, new constraint on anthropogenically forced climate models. It is unknown if the current generation of climate models, other than the PCM, meet this constraint.
A sample-guided approach to incremental structured web database crawling

Web database crawling is a promising solution for Deep Web data integration. To the best of our knowledge, the existing approaches only focused on how to crawl all records in a web database. Due to the high dynamic of most web databases, it is not practical to harvest a small proportion of new records by crawling the whole database. This paper studies the problem of incremental web database crawling, which targets at crawling the new records from a web database efficiently. In the proposed approach, a new graph model, query related graph, is proposed to transform a incremental crawling task into a graph traversal process. Based on this graph model, appropriate queries are generated for crawling which are guided by the samples of the web database. Extensive experimental evaluations over real Web databases validate the effectiveness of our techniques and provide insights for future efforts in this direction.
MODELING OF GENERALIZED UNIFIED POWER FLOW CONTROLLER FOR SUITABLE LOCATION AND POWER FLOW CONTROL

Modeling of generalized unified power flow controller (GUPFC), based on the static consideration, and has been presented in this paper used for power flow control. A Newton-Raphson load flow program has been developed which includes comprehensive control facilities and yet exhibits very strong convergence characteristics. The injection model, which is used to locate GUPFC suitably in the power system, is incorporated into an existing Newton-Raphson load flow algorithm in polar coordinate. The modified Jacobian matrix and power mismatch equations are deduced based on the injection model of GUPFC to control active and reactive powers and voltage magnitude in any combination or to control none of them. Test results are presented on IEEE 30-bus system, which demonstrate the effectiveness of the proposed method.
Topic Evolution in a Stream of Documents

Abstract Document collections evolve over time, new topics emerge and old ones decline. At the same time, the terminology evolves as well. Much literature is devoted to topic evolution in nite document sequences assuming a xed vocabulary. In this study, we propose \Topic Monitor" for the monitoring and understanding of topic and vocabulary evolution over an in nite document sequence, i.e. a stream. We use Probabilistic Latent Semantic Analysis (PLSA) for topic modeling and propose new folding-in techniques for topic adaptation under an evolving vocabulary. We extract a series of models, on which we detect index-based topic threads as human-interpretable descriptions of topic evolution.
Semantic Valence Modeling: Emotion Recognition and Affective States in Context-Aware Systems

Defining and describing a context requires knowledge (contextual information), while research is addressing a wider range of potential contextual information in a diverse range of domains the diversity of potential contextual information has not been effectively addressed. This paper considers the implementation of context and identifies emotion (more accurately emotional response) as a factor in the personalization of services as under-represented in the literature. We propose semantic valence modeling implemented in fuzzy rule-based systems as a potential solution to the implementation of emotional responses in context-aware systems. It is concluded that the effective implementation of emotional responses based on the posited approach will improve the accuracy of personalized service provision and additionally offers the potential to improve the levels of computational intelligence in context-aware domains and systems.
Faster and dynamic algorithms for maximal end-component decomposition and related graph problems in probabilistic verification

We present faster and dynamic algorithms for the following problems arising in probabilistic verification: Computation of the maximal end-component (mec) decomposition of Markov decision processes (MDPs), and of the almost sure winning set for reachability and parity objectives in MDPs. We achieve the following running time for static algorithms in MDPs with graphs of <i>n</i> vertices and <i>m</i> edges: (1) <i>O</i>(<i>m</i> · min{√<i>m, n</i><sup>2/3</sup>}) for the mec decomposition, improving the longstanding <i>O</i>(<i>m·n</i>) bound; (2) <i>O</i>(<i>m·n</i><sup>2/3</sup>) for reachability objectives, improving the previous <i>O</i>(<i>m</i> · √<i>m</i>) bound for <i>m</i> > <i>n</i><sup>4/3</sup>; and (3) <i>O</i>(<i>m</i> · min{ √<i>m,n</i><sup>2/3</sup> } · log(<i>d</i>)) for parity objectives with <i>d</i> priorities, improving the previous <i>O</i>(<i>m</i> · √<i>m</i> · <i>d</i>) bound. We also give incremental and decremental algorithms in linear time for mec decomposition and reachability objectives and <i>O</i>(<i>m</i> · log <i>d</i>) time for parity objectives.
A Novel Template Matching Scheme for Fast Full-Search Boosted by an Integral Image

A new template matching method accelerated by an integral image is proposed. In contrast to the conventional winner-update template matching algorithm, the proposed scheme uses an integral image instead of a block sum pyramid to represent the search area. When an integral image is used, block sums on the lowest level are evaluated very fast. As a result, the speed with which nonbest candidates are rejected is nearly double that of the conventional scheme. Moreover, the proposed scheme needs less memory than the conventional approach to maintain block sums of candidates and can be easily extended to nonsquare (rectangular) template matching.
A Gaussian Scale Space Approach For Exudates Detection, Classification And Severity Prediction

In the context of Computer Aided Diagnosis system for diabetic retinopathy, we present a novel method for detection of exudates and their classification for disease severity prediction. The method is based on Gaussian scale space based interest map and mathematical morphology. It makes use of support vector machine for classification and location information of the optic disc and the macula region for severity prediction. It can efficiently handle luminance variation and it is suitable for varied sized exudates. The method has been probed in publicly available DIARETDB1V2 and e-ophthaEX databases. For exudate detection the proposed method achieved a sensitivity of 96.54% and prediction of 98.35% in DIARETDB1V2 database.
Psychological Traits and Trading Strategies

This paper analyzes experimentally if psychological traits and cognitive biases affect trading behaviour and performance. Based on the answers of 67 subjects to a psychological questionnaire we measured their degree of overconfidence, impulsiveness and self-monitoring, and their availability, representativeness and confirmation biases. The 67 subjects also participated in an experimental financial market, in the spirit of Plott and Sunder (1988). We find that impulsive subjects tend to place more orders but do not incur larger losses. We also find that overconfident subjects and subjects prone to the confirmation and representativeness biases have a greater tendency to place unprofitable orders. This negative impact of cognitive biases on trading performance is sronger when subjects have acquired some experience of the game. This suggests that biased subjects engage in improper learning.
American Journal of Epidemiology Original Contribution Relation of Immediate Postnatal Growth with Obesity and Related Metabolic Risk Factors in Adulthood the Northern Finland Birth Cohort 1966 Study

The authors examined associations between postnatal growth velocity through age 2 years and metabolic outcomes at age 31 years in a population-based birth-cohort study of 3,778 Finns (1966–1998). Approximately 8 height measurements and 9 weight measurements were obtained from birth to age 2 years. Peak height velocity (PHV) and peak weight velocity (PWV) in infancy were derived from parametric growth curves fitted to longitudinal height and weight growth data. Body mass index (BMI), waist circumference (WC), high density lipoprotein (HDL) cholesterol, triglycerides, glucose, systolic and diastolic blood pressure (BP), and the metabolic syndrome were measured at age 31 years. PHV was significantly positively associated with systolic and diastolic BP and WC in adulthood. For each 8-cm/year (2-standard-deviation) increase in PHV, WC increased by 1.60 cm (95% confidence interval: 0.73, 2.46), after adjustment for potential confounders, including birth weight. PWV was significantly associated with adulthood systolic BP, WC, and BMI. A 4-kg/year higher PWV was associated with a 1.87-cm (95% confidence interval: 1.08, 2.65) larger WC in adulthood, after adjustment for potential confounders. HDL cholesterol (direct), triglycerides (inverse), and metabolic syndrome (inverse) displayed associations with PWV only after BMI was accounted for. These results showed that growth during the immediate postnatal period is associated with adulthood obesity and BP. Lifestyle changes from early life might be important in reducing adulthood obesity and high-BP risk. A dramatic rise in obesity and metabolic disorders has been observed in both developing countries and the developed world (1). An early life component is increasingly being recognized in the etiology of these disorders (2, 3). Patterns of growth associated with low birth weight and increased weight gain in childhood, as well as low birth weight per se, have shown consistent inverse associations with cardiovascular risk factors, insulin resistance, diabetes, and cardiovascular disease in adulthood (4–9). In contrast to birth weight and childhood growth trajec-tories, there has been little research on the relation of the immediate postnatal developmental period to cardiovascular and metabolic outcomes in adulthood. This is the period of the fastest growth in the entire life span and is a critical window of tissue and organ development wherein several regulatory mechanisms continue to develop after birth (10). Thus, variations in this process may have long-lasting effects on health. Several studies have examined weight changes between birth and the first year of life; results have suggested that weight gain is associated with childhood, adolescent, and adult …
Active Reward Learning

While reward functions are an essential component of many robot learning methods, defining such functions remains a hard problem in many practical applications. For tasks such as grasping, there are no reliable success measures available. Defining reward functions by hand requires extensive task knowledge and often leads to undesired emergent behavior. Instead, we propose to learn the reward function through active learning, querying human expert knowledge for a subset of the agent’s rollouts. We introduce a framework, wherein a traditional learning algorithm interplays with the reward learning component, such that the evolution of the action learner guides the queries of the reward learner. We demonstrate results of our method on a robot grasping task and show that the learned reward function generalizes to a similar task.
Development of Social Media GIS for Information Exchange between Regions

This study aims to develop a social media GIS (Geographic Information Systems) specially tailored to information exchange between regions. The conclusions of this study are summarized in the following three points. (1) Social media GIS is a geographic information system which integratesWeb-GIS, SNS and Twitter into a single system. A social media GIS was conducted for the collection of regional information in the eastern part of Yamanashi Prefecture. The social media GIS uses a design which displays its usefulness in multi-directional information transmission and in easing the limitations of space, time and continuity, making it possible to redesign systems in accordance with target cases. (2) During the operation of the social media GIS for about two months, most of the users were in their20s. Users exchanged regional information using the comment and button functions. (3)The system was evaluated based on the results of a questionnaire to users and an access analysis oflog data during operationin order to identify measures for improvement of the system. Because of users’ high evaluations of its original functions, the overall operability of the system was highly evaluated. Most of the contributed information was only known to local residents, and it was evident that the system fulfilled its intended role.
Low PAPR Filter Bank Single Carrier for 5G mMTC

Asynchronous transmission for 5G massive machine type communication (mMTC) reduces power consumption and provides longer battery life of mMTC devices compared to synchronous transmission because of less signaling interaction between the base station and mMTC devices. To reduce frequency leakage from other user devices, several waveforms based on modification on orthogonal frequency division multiple (OFDM) with low out-of-band (OOB) emission property has been proposed in 5G new radio. However, those waveforms are typically of high peak to average power ratio (PAPR) and it has been shown for those waveforms there is OOB emission regrowth for mMTC devices caused by nonlinear power amplify (PA). We propose a low PAPR filter bank single carrier frequency division multiple access (SC-FDMA) waveform, called LP-FBSC, which helps to resist OOB emission regrowth caused by nonlinear PA. Two filters are applied in one stream to achieve low PAPR and low OOB emission performance, where one filter is poly phase network (PPN) structure in time domain for low OOB emission purpose, and the other is applied at frequency domain with element-wise multiplication for low PAPR purpose. In addition, the proposed method introduces multiple streams for purpose of even further reduced PAPR, where the modulated data and filter coefficients of the other streams are determined from those of first stream. For Pi/2-BPSK and Pi/4-QPSK modulation, the PAPR for LP-FBSC can be as low as 2.6 dB and 4.2 dB while low OOB emission property being maintained.
.NET API Wrapping for Existing C++ Haptic APIs

For a long time haptic devices were expensive and therefore only accessible to a specialized community. But with companies like Novint Technologies introducing a peripheral intended to sell for about US$100, haptic devices can be expected to be affordable for a wider public. But considering that most haptic APIs are in C++, a language intended for expert programmers, novice programmers wanting to program haptic devices would face a steep learning curve. However, if the APIs were to be usable from within the . NET framework, it would allow the more novice users to program using over 20 programming languages and extensive programming solutions and therefore they would be able to easily and efficiently develop software with haptic capabilities. This paper presents a set of guidelines for a design architecture that would allow migrating an existing C++ API to the . NET framework without having to rewrite it from scratch. The presented architecture was implemented by wrapping the Sensable Ghost SDK 3.0. It was then used in both software and hardware based scenarios
StemNet: An Evolving Service for Knowledge Networking in the Life Sciences

Up until now, crucial life science information resources, whether bibliographic or factual databases, are isolated from each other. Moreover, semantic metadata intended to structure their contents is supplied in a manual form only. In the StemNet project we aim at developing a framework for semantic interoperability for these resources. This will facilitate the extraction of relevant information from textual sources and the generation of semantic metadata in a fully automatic manner. In this way, (from a computational perspective) unstructured life science documents are linked to structured biological fact databases, in particular to the identifiers of genes, proteins, etc. Thus, life scientists will be able to seamlessly access information from a homogeneous platform, despite the fact that the original information was unlinked and scattered over the whole variety of heterogeneous life science information resources and, therefore, almost inaccessible for integrated systematic search by academic, clinical, or industrial users.
Spectrum and connectivity aware anchor-based routing in cognitive vehicular ad hoc networks

In this paper, we propose the spectrum and connectivity aware anchor-based routing protocol for cognitive radio vehicular ad hoc networks (CR-VANETs). The protocol has two modes: decision mode and forwarding mode. Decision is taken at the junctions to select the path which is highly connected and which has common idle channels between communicating vehicles. In forwarding mode, vehicles select the next relay node based on channel state (idle/busy), distance, and link lifetime. We consider vehicle-to-vehicle communication in a city scenario for both connected and sparse networks. Our proposed protocol shows improvement in packet delivery ratio in comparison with existing protocol.
An Intercomparison of Verification Scores for Evaluating the Sea Ice Edge Position in Seasonal Forecasts

With the improving skill of sea ice forecasts, verification methods are becoming increasingly important to inform model developers and users. In this study, the Modified Hausdorff Distance (MHD), the Spatial Probability Score (SPS), and a variation of the SPS are compared in order to assess their performances for evaluating the ice edge position in the new European Centre for Medium‐Range Weather Forecasts seasonal forecasts (SEAS5). On average, the SEAS5 forecasts outperform a climatological reference during about 3 weeks using the MHD, and during about 5 weeks using the SPS. Furthermore, our results show that the MHD is more sensitive than the SPS to the presence of isolated sea ice patches. Moreover, the variation of the SPS introduced here is not seasonally dependent (contrary to the original SPS) and can be interpreted as a distance error of the ice edge position, which is a potentially relevant information for end users.