Miracle-dz/UniFAR-FTUs huggingface dataset:
Real-time false data injection attack detection in energy internet using online robust principal component analysis

In energy internet, electric power infrastructure is integrated with cyber infrastructure, which makes power grid vulnerable to cyberattack. Specially, when intruders know the configuration of the target power system, false data injection attacks can be successfully launched to bypass the traditional residual-based bad data detection system. In the presence of this dilemma, this paper aims to design a more robust and useful real-time false data injection attack detection mechanism applied in the supervisory control and data acquisition (SCADA) system in smart grid. Noticing the low dimensionality of temporal measurements of power grid states as well as the sparse nature of malicious attacks, robust principal component analysis (RPCA) is applied to false data injection attack detection in power grid and low-rank matrix fitting (LMaFit) is chosen as the solving algorithm. However, conventional RPCA is an offline method which confines its application, to meet the real-time requirement of power grid attack detection, by use of low-rank projection matrix, an online RPCA based detection mechanism is proposed, which returns detection results immediately as soon as new power grid measurements arrive and needs less computing time and storage space. Experiments on the SCADA test bed show that the proposed online RPCA based detection method works well and its performance on detecting and computing is better than the previous online PCA based method. Specially, the detection sensitivity of the proposed algorithm is 4 orders of magnitude higher than online PCA, and the calculation speed is improved by 2 to 3 orders of magnitude compared to offline RPCA.
Effect of dietary fibre on nitrogen retention and fibre associated threonine losses in growing pigs

Apart from being an energy source, dietary fibre is also discussed to act as anti-nutritional factor reducing apparent precaecal protein and amino acid (AA) digestibility due to reduced absorption or increased endogenous secretion or both. However, the amounts of protein and AA of endogenous origin determined at the terminal ileum in cannulated animals do not represent the total losses associated with endogenous secretion. A high proportion of secreted protein is reabsorbed and does not reach the terminal ileum, and losses occur during synthesis of endogenous protein. Therefore, the present study used an alternative indirect approach, taking the reduction of nitrogen (N) retention in a threonine (Thr) limited diet as a sensitive indicator for fibre-associated Thr losses. Two experiments were conducted with 12 castrated male pigs each between 37 and 75 kg body weight to measure the effect of the intake of Thr and 150 and 300 g/d fibre from wheat bran (Exp. 1), or 150 g/d fibre from rape seed, cassava leaves, and cassava root peels, respectively (Exp. 2), on N retention. During two (Exp. 1) and three (Exp. 2) balance periods the animals were subjected to the dietary treatments according to a cross-over design. All animals received 1350 g/d of a wheat–soybean-based diet supplemented with free AA to ensure Thr being the first-limiting AA. To determine the effect of Thr on N retention, intake of the basal diet was reduced to 1150 g/d and supplemented with corn starch to reach equal energy intake and an unchanged AA pattern. With increasing BW additional starch was added to all diets to ensure a constant energy intake of 1.25 MJ ME/kg BW0.75. Since the fibre sources contained small amounts of Thr, N retentions were corrected for precaecal digestible Thr intake originating from the fibre sources according to the Thr effect on N retention as determined in experiment 1. Corrected N retentions were affected by fibre level (p = 0.007) and source (p < 0.001). Fibre-associated Thr losses amounted to 3.3, 3.2, 1.2, and 1.1 g/kg fibre from wheat bran, rapeseed, cassava leaf, and cassava root peel, respectively. It is concluded that Thr losses per gram of dietary fibre depend on the fibre source and that fibre concentration and source in pig diets should be considered as a factor affecting Thr requirement.
Building Distant Supervised Relation Extractors

A well-known drawback in building machine learning semantic relation detectors for natural language is the lack of a large number of qualified training instances for the target relations in multiple languages. Even when good results are achieved, the datasets used by the state-of-the-art approaches are rarely published. In order to address these problems, this work presents an automatic approach to build multilingual semantic relation detectors through distant supervision combining two of the largest resources of structured and unstructured content available on the Web, DBpedia and Wikipedia. We map the DBpedia ontology back to the Wikipedia text to extract more than 100.000 training instances for more than 90 DBpedia relations for English and Portuguese languages without human intervention. First, we mine the Wikipedia articles to find candidate instances for relations described in the DBpedia ontology. Second, we preprocess and normalize the data filtering out irrelevant instances. Finally, we use the normalized data to construct regularized logistic regression detectors that achieve more than 80% of F-Measure for both English and Portuguese languages. In this paper, we also compare the impact of different types of features on the accuracy of the trained detector, demonstrating significant performance improvements when combining lexical, syntactic and semantic features. Both the datasets and the code used in this research are available online.
Practical Algorithms for Deciding Path Ordering Constraint Satisfaction

We introduce new algorithms for deciding the satisfiability of constraints for the full recursive path ordering with status (RPO), and hence as well for other path orderings like LPO, MPO, KNS and RDO, and for all possible total precedences and signatures. The techniques are based on a new notion of solved form, where fundamental properties of orderings like transitivity and monotonicity are taken into account. Apart from simplicity and elegance from the theoretical point of view, the main contribution of these algorithms is on efficiency in practice. Since guessing is minimized, and, in particular, no linear orderings between the subterms are guessed, a practical improvement in performance of several orders of magnitude over previous algorithms is obtained, as shown by our experiments.
Systems Analysis of Seed Filling in Arabidopsis: Using General Linear Modeling to Assess Concordance of Transcript and Protein Expression1[C][W][OA]

Previous systems analyses in plants have focused on a single developmental stage or time point, although it is often important to additionally consider time-index changes. During seed development a cascade of events occurs within a relatively brief time scale. We have collected protein and transcript expression data from five sequential stages of Arabidopsis (Arabidopsis thaliana) seed development encompassing the period of reserve polymer accumulation. Protein expression profiling employed two-dimensional gel electrophoresis coupled with tandem mass spectrometry, while transcript profiling used oligonucleotide microarrays. Analyses in biological triplicate yielded robust expression information for 523 proteins and 22,746 genes across the five developmental stages, and established 319 protein/transcript pairs for subsequent pattern analysis. General linear modeling was used to evaluate the protein/transcript expression patterns. Overall, application of this statistical assessment technique showed concurrence for a slight majority (56%) of expression pairs. Many specific examples of discordant protein/transcript expression patterns were detected, suggesting that this approach will be useful in revealing examples of posttranscriptional regulation.
Are Depressive Episodes Different in Bipolar Disorder type I, type II and Unipolar Depression?

Amaç: Bu çalışmanın amacı, iki uçlu tip I (İUB-I), tip II (İUB-II) ve tek uçlu bozukluk (TUB) depresif dönemleri arasındaki farklılıkları incelemektir. Yöntem: Bu amaçla çalışmamızda yatarak ya da ayaktan tedavi gören, DSM-IV’e göre İUB-I depresif dönem ölçütlerini karşılayan 49, İUB-II depresif dönem ölçütlerini karşılayan 47 ve majör depresif bozukluk (MDB) tanılı 46 olgu ardışık olarak değerlendirilmiştir. Olgularda şimdiki depresif dönem için tedavi düzenlenmemiş olma şartı aranmıştır. Tanı görüşmeleri SCID-I ile yapılmış, hasta ve hastalığa ilişkin bilgiler SKIP-TURK ile kaydedilmiştir. Her bir olguya, Hamilton Depresyon Ölçeği (HDDÖ), İntihar Niyeti Ölçeği (İNO), Barratt İmpusivite Ölçeği (BİS), Yeme tutumu Envanteri (YTE), Pittsburgh Uyku Kalitesi İndeksi (PUKİ) ve Arizona Cinsel Yaşantılar Ölçeği (ASEX) uygulanmıştır. Bulgular: Melankolik belirtiler gösteren alt tip ve psikotik bulgu, İUB-I tanılı olgular arasında, atipik belirtiler gösteren alt tip ve özkıyım girişimi İUB-II tanılı olgular arasında daha sık bulunmuştur. Ani başlangıç ve mevsimsellik İUB-II tanılı olgular arasında en yüksek sıklıkta saptanmıştır. HDDÖ maddeleri tek tek karşılaştırıldığında 5. , 6. , 14. ve 17. madde (orta ve son uykusuzluk, genital belirtiler ve içgörü) dışındaki maddeler gruplar arasında farklılık göstermiştir. TUB tanılı olgularda HDDÖ ve BİS puanları arasında güçlü, İUB-I tanılı olgularda BİS ve PUKİ puanları arasında, İUB-II tanılı olgularda ise BİS ve YTE puanları arasında orta derecede bir ilişki vardır. Sonuç: Depresif dönem, duygudurum bozuklukları arasında bazı benzerlikler gösterse de, ayırıcı tanı ve tedavi yönünden yararlı olabilecek belirgin farklılıklar bulundurmaktadır.
Maternal Obesity Induced by Diet in Rats Permanently Influences Central Processes Regulating Food Intake in Offspring

Hypothalamic systems which regulate appetite may be permanently modified during early development. We have previously reported hyperphagia and increased adiposity in the adult offspring of rodents fed an obesogenic diet prior to and throughout pregnancy and lactation. We now report that offspring of obese (OffOb) rats display an amplified and prolonged neonatal leptin surge, which is accompanied by elevated leptin mRNA expression in their abdominal white adipose tissue. At postnatal Day 30, before the onset of hyperphagia in these animals, serum leptin is normal, but leptin-induced appetite suppression and phosphorylation of STAT3 in the arcuate nucleus (ARC) are attenuated; the level of AgRP-immunoreactivity in the hypothalamic paraventricular nucleus (PVH), which derives from neurones in the ARC and is developmentally dependent on leptin, is also diminished. We hypothesise that prolonged release of abnormally high levels of leptin by neonatal OffOb rats leads to leptin resistance and permanently affects hypothalamic functions involving the ARC and PVH. Such effects may underlie the developmental programming of hyperphagia and obesity in these rats.
Brainstem abnormalities in attention deficit hyperactivity disorder support high accuracy individual diagnostic classification

Despite extensive research, psychiatry remains an essentially clinical and, therefore, subjective clinical discipline, with no objective biomarkers to guide clinical practice and research. Development of psychiatric biomarkers is consequently important. A promising approach involves the use of machine learning with neuroimaging, to make predictions of diagnosis and treatment response for individual patients. Herein, we describe predictions of attention deficit hyperactivity disorder (ADHD) diagnosis using structural T1 weighted brain scans obtained from 34 young males with ADHD and 34 controls and a support vector machine. We report 93% accuracy of individual subject diagnostic prediction. Importantly, automated selection of brain regions supporting prediction was used. High accuracy prediction was supported by a region of reduced white matter in the brainstem, associated with a pons volumetric reduction in ADHD, adjacent to the noradrenergic locus coeruleus and dopaminergic ventral tegmental area nuclei. Medications used to treat ADHD modify dopaminergic and noradrenergic function. The white matter brainstem finding raises the possibility of “catecholamine disconnection or dysregulation” contributing to the ADHD syndrome, ameliorated by medication. Hum Brain Mapp 35:5179–5189, 2014. © 2014 Wiley Periodicals, Inc.
No News is Good News in Climate Change?

We develop a tractable climate-economy model for evaluating a price for carbon when climate change impacts are non-existing – they may arrive later. We identify the general-equilibrium value of learning (or not learning) the economic losses from impacts. The value justifies increasing carbon prices due to increasing vulnerability to impacts when the global economy expands, although the assessment of climate change becomes more optimistic. The model produces a belief distribution for the social cost of carbon that can be calibrated to match a comprehensive survey of previous estimates. Even if climate change progresses without impacts for the coming century, the carbon price continues to increase as suggested by the “climate policy ramp” of existing evaluations. The quantitative assessment justifies climate policies for a rational skeptic. (JEL classification: H43; H41; D61; D91; Q54; E21.
Description Logics for Modelling Dynamic Information

In the first part of this Chapter we will introduce a general temporally enhanced conceptual data model able to represent time varying data, in the spirit of a temporally enhanced Entity-Relationship data model. In the second part, we will introduce an object-oriented conceptual data model enriched with schema change operators, which are able to represent the explicit temporal evolution of the schema while maintaining a consistent view on the (static) instantiated data. We will introduce a provably correct encoding of both conceptual data models and their inference problems in Description Logics. In this way, we study the properties of both the temporal conceptual data model and the object-oriented data model with schema change facilities.
xLink: Context Management Solution for Commodity Ubiquitous Computing Environments

In this position paper, we present xLink, a system for managing context information and marshalling service queries and data flow. The repeated re-invention of context management systems remains a perennial phenomenon in context aware and ubiquitous computing. Often, these systems are integrated into applications to accommodate the low level requirements of the underlying devices. We hope to address this issue by providing a framework that allows a clean, API-based separation of device, context, and service management functionalities without curtailing the capabilities of any segment. xLink is designed to allow commodity ubiquitous computing devices, particularly devices with highly constrained computational capabilities, to interface directly at a low level to the context management framework, while still providing a clean and versatile service Application Programming Interface (API) that allows applications maximum expressive freedom. We also present a usage scenario for technologies based on xLink, and discuss the strengths and shortcomings of our approach in relation to other context and information flow management strategies.
Utilitarian Approach to Privacy in Distributed Constraint Optimization Problems

Privacy has been a major motivation for distributed problem optimization. However, even though several methods have been proposed to evaluate it, none of them is widely used. The Distributed Constraint Optimization Problem (DCOP) is a fundamental model used to approach various families of distributed problems. Here we approach the problem by letting both the optimized costs found in DCOPs and the privacy requirements guide the agents’ exploration of the search space. We introduce Utilitarian Distributed Constraint Optimization Problem (UDCOP) where the costs and the privacy requirements are used as parameters to a heuristic modifying the search process. Common stochastic algorithms for decentralized constraint optimization problems are evaluated here according to how well they preserve privacy.
Reversing Control of a Car with a Trailer Using the Driver Assistance System

Passive trailer systems provide a variety of advantages in delivery and transportation applications. The transportation capacity of the truck with multiple trailers can be increased in proportion to the number of trailers. The cost of the car with trailers is much lower than the cost of multiple cars. However, the major drawback of the trailer system is that the control problem is difficult. We concentrate on the motion control problem of “pushing” trailers because pushing is much more difficult than “pulling”. In this paper, it is shown how the car with passive trailers can be easily controlled by the use of the proposed driver assist system and the motion control scheme. Since the keypad is the only additional device for the driver assist system, the proposed scheme can be implemented with the conventional trucks without many hardware modifications. The manual control strategy of pushing is established. The kinematic design of the passive trailer is adopted from the prior work (Park and Chung, 2004). The kinematic configuration design of the car with trailers is proposed for pushing control. The usefulness of the proposed scheme is experimentally verified with the small scale car with trailer system for the car parking problem. The parking control requires forward and reverse motion in narrow environment. It is shown that even beginners can easily control the pushing motion with the proposed scheme.
Histochemical and morpho-metrical study of mouse intestine epithelium after a long term diet containing genetically modified soybean

Diet can influence the structural characteristics of both small and large intestine. In this study, we investigated the duodenum and colon of mice fed on genetically modified (GM) soybean during their whole life span (1–24 months) by focusing our attention on the histological and ultrastructural characteristics of the epithelium, the histochemical pattern of goblet cell mucins, and the growth profile of the coliform population. Our results demonstrate that controls and GM-soybean fed mice are similarly affected by ageing. Moreover, the GM soybean-containing diet does not induce structural alterations in duodenal and colonic epithelium or in coliform population, even after a long term intake. On the other hand, the histochemical approach revealed significant diet-related changes in mucin amounts in the duodenum. In particular, the percentage of villous area occupied by acidic and sulpho-mucin granules decreased from controls to GM-fed animals, whereas neutral mucins did not change.
Do Cannabinoids Confer Neuroprotection Against Epilepsy? An Overview

Objective: Cannabinoid-based medications provide not only relief for specific symptoms, but also arrest or delay of disease progression in patients with pain, multiple sclerosis, and other conditions. Although they also seem to hold potential as anticonvulsant agents, evidence of their efficacy in epilepsy is supported by several evidences. Method: The data reviewed herein lend support to the notion that the endocannabinoid signalling system plays a key modulation role in the activities subserved by the hippocampus, which is directly or indirectly affected in epilepsy patients. Conclusion: The notion is supported by a variety of anatomical, electrophysiological, biochemical and pharmacological findings. These data suggest the need for developing novel treatments using compounds that selectively target individual elements of the endocannabinoid signalling system.
CPA-SLAM: Consistent plane-model alignment for direct RGB-D SLAM

Planes are predominant features of man-made environments which have been exploited in many mapping approaches. In this paper, we propose a real-time capable RGB-D SLAM system that consistently integrates frame-to-keyframe and frame-to-plane alignment. Our method models the environment with a global plane model and - besides direct image alignment - it uses the planes for tracking and global graph optimization. This way, our method makes use of the dense image information available in keyframes for accurate short-term tracking. At the same time it uses a global model to reduce drift. Both components are integrated consistently in an expectation-maximization framework. In experiments, we demonstrate the benefits our approach and its state-of-the-art accuracy on challenging benchmarks.
Ieee Transactions on Visualization and Computer Graphics 1 Automated Analytical Methods to Support Visual Exploration of High-dimensional Data

—Visual exploration of multivariate data typically requires projection onto lower-dimensional representations. The number of possible representations grows rapidly with the number of dimensions, and manual exploration quickly becomes ineffective or even unfeasible. This paper proposes automatic analysis methods to extract potentially relevant visual structures from a set of candidate visualizations. Based on features, the visualizations are ranked in accordance with a specified user task. The user is provided with a manageable number of potentially useful candidate visualizations, which can be used as a starting point for interactive data analysis. This can effectively ease the task of finding truly useful visualizations and potentially speed up the data exploration task. In this paper, we present ranking measures for class-based as well as non class-based scatterplots and parallel coordinates visualizations. The proposed analysis methods are evaluated on different datasets.
Unraveling the Mystery of Institutionalization.

Whether or not a program becomes a durable part of the curriculum depends on teacher mastery and commitment and administrative action as well as other factors. hese two schools "-crc part of ao inteisise study of 12 cclmnicntarx and secondary sclhools included in the Study of Disscminatioin IEfforts Supporting School Improscnicilt iCranldall and associates, 1982: Hubcrnlan and \liles, 19821 In both schools. the iiiosatiou ~sas being carried out effcctisclx. \Yet a ycar later, oe schiool's program, like itllan) "ness things. " had disappeared. TIhe other had conitinrued, by soiieho;N getting "built ili" to the life of the school Why does this institutiolnalization oc-
Grouping and aggregation in the concept-oriented data model

In the paper we describe the problem of grouping and aggregation in the concept-oriented data model. The model is based on ordering its elements within a hierarchical multidimensional space. This order is then used to define all its main properties and mechanisms. In particular, it is assumed that elements positioned higher are interpreted as groups for their lower level elements. Two operations of projection and de-projection are defined for one-dimensional and multidimensional cases. It is demonstrated how these operations can be used for multidimensional analysis.
Probability Concepts for an Expert System Used for Data Fusion

Probability concepts for ruled-based expert systems are developed that are compatible with probability used in data fusion of imprecise information. Procedures for treating probabilistic evidence are presented, which include the effects of statistical dependence. Confidence limits are defined as being proportional to root-mean-square errors in estimates, and a method is outlined that allows the confidence limits in the probability estimate of the hypothesis to be expressed in terms of the confidence limits in the estimate of the evidence. Procedures are outlined for weighting and combining multiple reports that pertain to the same item of evidence. The illustrative examples apply to tactical data fusion, but the same probability procedures can be applied to other expert systems.