Miracle-dz/UniFAR-FTUs huggingface dataset:
Longitudinal Changes in the Government-Certified Index Stage and Requisite Costs for Long-Term Care Insurance System among the Community-Dwelling Demented Elderly in Japan

Background. A new public long-term care (LTC) insurance was launched in 2000 in Japan. However, there have been few studies involving factors that increase LTC costs of demented subjects; no follow-up studies involving the Government-Certified Index (GCI) and requisite costs related to the causes of dementia. Method. An epidemiological survey was conducted in a rural area in Japan in 1999, and 271 subjects were diagnosed as dementia patients. Age, sex, mini-mental state examination, clinical dementia rating, activity of daily living, causes of dementia, and coexisting physical disease were confirmed. After the LTC insurance has been launched, we tracked the GCI stages and payment amounts every month for 8 years. Result. 209 subjects were certified to be eligible for LTC insurance; however, 13 did not receive any payment. Only 49 out of 209 were alive after the follow-up period. The most common cause of dementia was Alzheimer's disease (AD), followed by vascular dementia (VaD). There was no significant difference between the mortality rates of the two groups. VaD subjects required higher costs than AD subjects in the total certified period and in GCI stage 5. Conclusion. Our results indicate that causes of dementia can have an impact on the requisite costs for the LTC insurance.
GPU-Aware Genetic Estimation of Hidden Markov Models for Workload Classification Problems

Hidden Markov models (HMM) have been an important analysis framework in many computer science applications. The estimation of the HMM parameters is crucial as regards the performance of the whole HMM. Generally, HMM parameters estimation is performed with iterative algorithm like the Baum-Welch method, or gradient based methods. The advantage of the iterative algorithms is their computational efficiency. The disadvantage is that their performance depend on the initial value of the parameters and thus they usually yield to local optimum parameter values. In this paper, a Genetic Algorithm (GA) is used to compute optimized HMM parameters. The algorithm has been implemented on a GPU to face the high demand of computational resources of GA. We used this optimized computation of HMM parameters in a process workload classification, and we made experimental assessment and analysis via using the well-known SPEC-2006 benchmarks. The obtained classification accuracy is significantly better than that obtained with the Baum-Welch algorithms. On the other hand, the time needed to obtain the HMM parameters is of the same order than that required by Baum-Welch algorithm.
Metabolomic Biomarkers of Prostate Cancer: Prediction, Diagnosis, Progression, Prognosis, and Recurrence

Metabolite profiling is being increasing employed in the study of prostate cancer as a means of identifying predictive, diagnostic, and prognostic biomarkers. This review provides a summary and critique of the current literature. Thirty-three human case–control studies of prostate cancer exploring disease prediction, diagnosis, progression, or treatment response were identified. All but one demonstrated the ability of metabolite profiling to distinguish cancer from benign, tumor aggressiveness, cases who recurred, and those who responded well to therapy. In the subset of studies where biomarker discriminatory ability was quantified, high AUCs were reported that would potentially outperform the current gold standards in diagnosis, prognosis, and disease recurrence, including PSA testing. There were substantial similarities between the metabolites and the associated pathways reported as significant by independent studies, and important roles for abnormal cell growth, intensive cell proliferation, and dysregulation of lipid metabolism were highlighted. The weight of the evidence therefore suggests metabolic alterations specific to prostate carcinogenesis and progression that may represent potential metabolic biomarkers. However, replication and validation of the most promising biomarkers is currently lacking and a number of outstanding methodologic issues remain to be addressed to maximize the utility of metabolomics in the study of prostate cancer. Cancer Epidemiol Biomarkers Prev; 25(6); 887–906. ©2016 AACR.
A N I NTELLIGENT E MBEDDED S YSTEM FOR P AY P HONES TO D ETECT C YBER C RIMES

This paper proposes a mechanism which is used to provide security against the threats given to the patrols through the coin pay call access system. In this case the details of the person doing this offense is needed it can be obtained through this proposed system. This is executed using the image processing unit where the image and the biometric details of the person dialling the police station is captured and processed then it is sent to the networking unit and database unit where the image is compared with the nationalised database in the central processing unit using NIDR processor. The overall theme of this proposal is to build a system which can eliminate the illegal act of causing threatening by providing false information to the patrols. The challenge in this process is to develop the system by using the advanced techniques in the process gathering information and processing it to the control room if requested for the further investigations.
Causal Link between Microsatellite Instability and hMRE11 Dysfunction in Human Cancers

Maintenance of genomic integrity is essential for cell survival, and genomic instability is a commonly recognized intrinsic property of all cancers. Microsatellite instability (MSI) represents a frequently occurring and easily traceable simple form of sequence variation, signified by the contraction or expansion of specific DNA sequences containing short tandem repeats. MSI is frequently detected in tumor cells with DNA mismatch repair (MMR) deficiency. It is commonly conceived that instability at individual microsatellite loci can arise spontaneously in cells independent of MMR status, and different microsatellite loci are generally not affected uniformly by MMR deficiency. It is well recognized that MMR deficiency per se is not sufficient to initiate tumorigenesis; rather, the biological effects have to be exerted by mutations in genes controlling cell survival, DNA damage response, and apoptosis. Recently, shortening of an intronic hMRE11 poly(T)11 tract has been associated with MMR deficiency, raising the possibility that hMRE11 may be inactivated by defective MMR. However, the molecular nature underlying this association is presently unknown, and review of the current literature suggests that hMRE11 is most likely involved with the MMR pathway in a more complex fashion than simply being a MMR target gene. An alternative scenario is proposed to better reconcile the differences among various studies. The potential role of hMRE11 in telomere repeats stability is also discussed. Mol Cancer Res; 9(11); 1443–8. ©2011 AACR.
Hand in Hand: Public Endorsement of Climate Change Mitigation and Adaptation

This research investigated how an individual’s endorsements of mitigation and adaptation relate to each other, and how well each of these can be accounted for by relevant social psychological factors. Based on survey data from two European convenience samples (N = 616 / 309) we found that public endorsements of mitigation and adaptation are strongly associated: Someone who is willing to reduce greenhouse gas emissions (mitigation) is also willing to prepare for climate change impacts (adaptation). Moreover, people endorsed the two response strategies for similar reasons: People who believe that climate change is real and dangerous, who have positive attitudes about protecting the environment and the climate, and who perceive climate change as a risk, are willing to respond to climate change. Furthermore, distinguishing between (spatially) proximal and distant risk perceptions suggested that the idea of portraying climate change as a proximal (i.e., local) threat might indeed be effective in promoting personal actions. However, to gain endorsement of broader societal initiatives such as policy support, it seems advisable to turn to the distant risks of climate change. The notion that “localising” climate change might not be the panacea for engaging people in this domain is discussed in regard to previous theory and research.
A Genetic Explanation for No Sex Difference in Spatial Ability among Eskimos

Superior spatial ability may be inherited as an X-linked recessive trait. Since the sex ratio for an X-linked recessive trait depends on the gene frequency of the recessive allele, the absence of a sex difference in Eskimo spatial ability may reflect an unusually high frequency of the recessive allele in the Eskimo population.
A Response Time Model For Bottom-Out Hints as Worked Examples

Students can use an educational system’s help in unexpected ways. For example, they may bypass abstract hints in search of a concrete solution. This behavior has traditionally been labeled as a form of gaming or help abuse. We propose that some examples of this behavior are not abusive and that bottom-out hints can act as worked examples. We create a model for distinguishing good student use of bottom-out hints from bad student use of bottom-out hints by means of logged response times. We show that this model not only predicts learning, but captures behaviors related to self-explanation.
The pattern of ocular dominance columns in cat primary visual cortex: intra‐ and interindividual variability of column spacing and its dependence on genetic background

We present a comprehensive analysis of the intrinsic variability of the periodicity of ocular dominance columns in cat primary visual cortex (area 17) and its relationship to genetic background and visual experience. We characterized the intra‐areal and interindividual variability of column spacing in a large set (n = 49) of ocular dominance patterns adapting a recently developed technique for the two‐dimensional analysis of orientation column patterns. Patterns were obtained from three different cat colonies (termed F, M and D), the cats having either normal visual experience or experimentally induced strabismus. Two‐dimensional maps of local column spacing were calculated for every pattern. In individual cortices, local column spacings varied by > 50% with the majority of column spacings ranging between 0.6 and 1.5 mm in different animals. In animals from colonies F and M (n = 29), the mean column spacing ranged between 1.03 and 1.27 mm and exhibited no significant differences, either between the two breeds or between strabismic and normal animals. The mean spacing was moderately clustered in the left and right brain hemisphere of individual animals but not in littermates. In animals from colony D (n = 2), average column spacing ranged between 0.73 and 0.95 mm, and was thus significantly different from the distribution of spacings in animals from breeds F and M, suggesting an influence of genetic factors on the layout of ocular dominance columns. Local column spacing exhibited a considerable systematic intra‐areal variation, with largest spacings along the representation of the horizontal meridian and smallest spacings along the peripheral representation of the vertical meridian. The total variability of ocular dominance column spacing comprised 24% systematic intra‐areal variation, 18% interindividual differences of mean column spacing and 58% nonsystematic intra‐areal variability.
Reactive noninterference

Many programs operate reactively--patiently waiting for user input, running for a while producing output, and eventually returning to a state where they are ready to accept another input (or occasionally diverging). When a reactive program communicates with multiple parties, we would like to be sure that it can be given secret information by one without leaking it to others. Motivated by web browsers and client-side web applications, we explore definitions of noninterference for reactive programs and identify two of special interest--one corresponding to termination-insensitive noninterference for a simple sequential language, the other to termination-sensitive noninterference. We focus on the former and develop a proof technique for showing that program behaviors are secure according to this definition. To demonstrate the viability of the approach, we define a simple reactive language with an information-flow type system and apply our proof technique to show that well-typed programs are secure.
Tailored Aggregation for Classification

Compression and variable selection are two classical strategies to deal with large-dimension data sets in classification. We propose an alternative strategy, called aggregation, which consists of a clustering step of redundant variables and a compression step within each group. We develop a statistical framework to define tailored aggregation methods that can be combined with selection methods to build reliable classifiers that benefit from the information contained in redundant variables. Two algorithms are proposed for ordered and nonordered variables, respectively. Applications to the kNN and CART algorithms are presented.
An Automatic Framework for Textured 3D Video-Based Facial Expression Recognition

Most of the existing research on 3D facial expression recognition has been done using static 3D meshes. 3D videos of a face are believed to contain more information in terms of the facial dynamics which are very critical for expression recognition. This paper presents a fully automatic framework which exploits the dynamics of textured 3D videos for recognition of six discrete facial expressions. Local video-patches of variable lengths are extracted from numerous locations of the training videos and represented as points on the Grassmannian manifold. An efficient graph-based spectral clustering algorithm is used to separately cluster these points for every expression class. Using a valid Grassmannian kernel function, the resulting cluster centers are embedded into a Reproducing Kernel Hilbert Space (RKHS) where six binary SVM models are learnt. Given a query video, we extract video-patches from it, represent them as points on the manifold and match these points with the learnt SVM models followed by a voting based strategy to decide about the class of the query video. The proposed framework is also implemented in parallel on 2D videos and a score level fusion of 2D & 3D videos is performed for performance improvement of the system. The experimental results on BU4DFE data set show that the system achieves a very high classification accuracy for facial expression recognition from 3D videos.
Armonique: Experiments in Content-Based Similarity Retrieval using Power-Law Melodic and Timbre Metrics

This paper presents results from an on-going MIR study utilizing hundreds of melodic and timbre features based on power laws for content-based similarity retrieval. These metrics are incorporated into a music search engine prototype, called Armonique. This prototype is used with a corpus of 9153 songs encoded in both MIDI and MP3 to identify pieces similar to and dissimilar from selected songs. The MIDI format is used to extract various powerlaw features measuring proportions of music-theoretic and other attributes, such as pitch, duration, melodic intervals, and chords. The MP3 format is used to extract power-law features measuring proportions within FFT power spectra related to timbre. Several assessment experiments have been conducted to evaluate the effectiveness of the similarity model. The results suggest that power-law metrics are very promising for content-based music querying and retrieval, as they seem to correlate with aspects of human emotion and aesthetics.
Distribution of Heavy Metals (Ni, Co, Pb, Cd, Hg) in Tissues of European Chub (Squalius cephalus L.) from the Middle Course of the Nitra River, Slovakia

Abstract The aim of this study was to determine the levels of Ni, Co, Pb, Cd and Hg in the muscle, hepatopankreas, kidney and gonads of European chub (Squalius cephalus) from the middle course of the Nitra River, during spring and autumn seasons by AAS method. The concentrations of metals (mg.kg-1 wet weight) in the muscle ranged as follows: Ni 0.15-1.18, Co 0.09-0.58, Pb 0.39-1.66, Cd 0.04-0.29, Hg 0.85-2.71. Statistically significant differences among individual tissues, as well as between seasons have been recorded. Higher metals concentrations were detected in inner organs than in muscle. Permissible limits for safe consumption in the case of Pb, Cd and Hg have been exceeded in 100%, 95% and 100%, respectively. Currently, for the Co and Ni are not set any permissible limits.
A reference comments crawler for assisting research paper writing

When writing a research paper, significant effort is spent comparing the current work to other related studies. In general, these comparisons comprise the 'Related Work' section of the paper, with the relevant reference papers cited and analyzed. An automatic method for gathering and managing information about other researchers' reviews of reference papers would reduce the time and effort needed for such comparisons. Thus, in this paper, we propose a crawler that gathers the comments made by other researchers on the papers that are cited in the 'Related Work' section and listed in the 'Bibliography' or 'References' section of a research paper. The Reference Comments Crawler (RCC) system collects the text pertaining to the reference papers, providing useful information to researchers by extracting relevant data from the comments. The RCC considers different types of reference identifiers and the comment sentences are extracted based on these reference identifiers and user-defined extraction rule. Also, the RCC system extracts and provides the previous and subsequent sentences, labeled as PreSentences and PostSentences, as well as the comment sentences including the reference identifier. A series of experiments were performed to evaluate precision and recall, and the results showed that the RCC system can provide useful information with a high degree of precision and recall to the user. Furthermore, through these experiments, our system can assist researchers by reducing the time and effort spent comparing and analyzing related work.
ATLAS - Human Language Technologies integrated within a Multilingual Web Content Management System

The main purpose of the project ATLAS (Applied Technology for Language-Aided CMS) is to facilitate multilingual web content development and management. Its main innovation is the integration of language technologies within a web content management system. The language processing framework, integrated with web content management, provides automatic annotation of important words, phrases and named entities, suggestions for categorisation of documents, automatic summary generation, and machine translation of summaries of documents. A machine translation approach, as well as methods for obtaining and constructing training data for machine translation are under development.
Low-Power and Widely Tunable Linearized Biquadratic Low-Pass Transconductor-C Filter

A sixth-order low-pass transconductor-C filter with a very wide tuning range (fc = 100 Hz to 10 MHz) is presented. The wide tuning range has been achieved without using switchable components or programmable building blocks. A single-stage folded cascode transconductor is employed to implement the proposed filter. A modified biquadratic topology is introduced to improve linearity performance of the filter over its tuning range. Power consumption of the filter scales linearly with cutoff frequency (60 pW/Hz/pole). Implemented in 0.18-μm complementary metal-oxide-semiconductor technology, the filter exhibits relatively constant noise and linearity performance over its entire tuning range and occupies a silicon area of 0.16 mm2 (0.027 mm2/pole).
Utilization of dimensionality reduction in stacked generalization architecture

Stacked Generalization (SG) is a hierarchical architecture, which combines classifiers in order to boost the performance of overall system by integrating the individual classifiers. Two-layered version of SG has been utilized in many image analysis researches and shown to be an effective tool for enhancing the performance measure of the individual classifiers in a number of various cases. However, due to its layered architecture and integration approach, it inherits some problems such as curse of dimensionality, i.e. necessity for more samples, and higher computational time for classification. In this work, the effect of two different dimensionality reduction methods, namely linear and non-linear, between layers of SG are analyzed to attack the curse of dimensionality problem. In the experimental part, the comparisons of these approaches with respect to each other and SG-without-dimensionality-reduction are presented. According to test results, it is concluded that dimensionality reduction has a positive effect on the performance of SG, i.e. both linear and nonlinear dimensionality reduction approaches performs better than SG architecture, and nonlinear dimensionality reduction achieves better classification accuracy than linear dimensionality reduction.
Physical Processes Associated with Heavy Flooding Rainfall in Nashville, Tennessee, and Vicinity during 1–2 May 2010: The Role of an Atmospheric River and Mesoscale Convective Systems*

AbstractA multiscale analysis is conducted in order to examine the physical processes that resulted in prolonged heavy rainfall and devastating flash flooding across western and central Tennessee and Kentucky on 1–2 May 2010, during which Nashville, Tennessee, received 344.7 mm of rainfall and incurred 11 flood-related fatalities. On the synoptic scale, heavy rainfall was supported by a persistent corridor of strong water vapor transport rooted in the tropics that was manifested as an atmospheric river (AR). This AR developed as water vapor was extracted from the eastern tropical Pacific and the Caribbean Sea and transported into the central Mississippi Valley by a strong southerly low-level jet (LLJ) positioned between a stationary lee trough along the eastern Mexico coast and a broad, stationary subtropical ridge positioned over the southeastern United States and the subtropical Atlantic. The AR, associated with substantial water vapor content and moderate convective available potential energy, supporte.
Evaluation of Kinect depth sensor for use in mobile robotics

To autonomously navigate through unstructured environment mobile robots rely mainly on vision systems. Commonly used are stereo vision, laser and infrared sensors. This paper deals with an evaluation of the Kinect depth sensor and compares it with stereo vision. Also the depth resolution, the accuracy and the repeatability have been determined throughout several experiments based on the SDK of Code Laboratories (CL) for Windows 7. Our experimental results show that the Kinect has a maximum depth resolution of 1.3[mm/color value] and a maximum accuracy of 0.02%. Also, depth density has been assessed and compared to stereo vision images, concluding several benefits the Kinect brings to the field of mobile robotics. Finally, suggestions are being made for several applications for use in mobile robotics
Mixing expressiveness and efficiency in a manufacturing planner

The application of artificial intelligence planning techniques to real world problems is a very difficult task which usually implies overcoming expressiveness and efficiency handicaps. Expressiveness in order to cope with the great amount of knowledge involved in these problems and also to obtain results directly, or almost directly, applicable in the field of study. Efficiency to achieve a good course through the potentially enormous search spaces and, therefore, a satisfactory response capability. This work describes MACHINE, a manufacturing planning architecture which is able to obtain sequential control programs for manufacturing systems, the steps given to overcome these expressiveness and efficiency handicaps and how it is able to solve some real size problems.