Miracle-dz/UniFAR-FTUs huggingface dataset:
Generalized functional linear models

We propose a generalized functional linear regression model for a regression situation where the response variable is a scalar and the predictor is a random function. A linear predictor is obtained by forming the scalar product of the predictor function with a smooth parameter function, and the expected value of the response is related to this linear predictor via a link function. If, in addition, a variance function is speciﬁed, this leads to a functional estimating equation which corresponds to maximizing a functional quasi-likelihood. This general approach includes the special cases of the functional linear model, as well as functional Poisson regression and functional binomial regression. The latter leads to procedures for classiﬁcation and discrimination of stochastic processes and functional data. We also consider the situation where the link and variance functions are unknown and are estimated nonparametrically from the data, using a semiparametric quasi-likelihood procedure. An essential step in our proposal is dimension reduction by approximating the predictor processes with a truncated Karhunen–Lo`eve expansion. We develop asymptotic inference for the proposed class of generalized regression models. In the proposed asymptotic approach, the truncation parameter increases with sample size, and a martingale central limit theorem is applied to establish the resulting increasing dimension asymptotics. We establish asymptotic normality for a properly scaled distance between estimated and true functions that corresponds to a suitable L 2 metric and is deﬁned through a generalized covariance operator. As a consequence, we obtain asymptotic tests and simultaneous conﬁdence bands for the parameter function that determines the gated in a simulation study. We ﬁnd that the practical selection of the number of components works well with the AIC criterion, and this ﬁnding is supported by theoretical considerations. We include an application to the classiﬁcation of medﬂies regarding their remaining longevity status, based on the observed initial egg-laying curve for each of 534 female medﬂies.
Pedagogical, institutional and human factors influencing the widespread adoption of educational technology in higher education

This paper will present an analysis of the factors which influence the adoption of educational technology in higher education. It will consider the characteristics of different types of educational technology, in terms of interactions between students and other students, educators, resources and computers. It will also consider what is known about learning in higher education, claiming that learning environments should be student-centric, knowledge-centric, assessment-centric and community-centric. The paper then considers the way that educational technology can effectively facilitate learning, through a deep-learning, student-centred, outcomes-based approach, focusing on learning activities. It argues that educational technology is mature enough from a technical perspective, and we know enough about how to design effective educational technology environments, but this knowledge is not widely applied. Weaknesses in project management and teamwork factors have impacted on project success in the past, but these issues are also well understood if not widely applied. Finally, the paper discusses research about institutional and human factors which impact on adoption of new technologies in higher education, identifying several human factors which influence adoption. The paper concludes that these issues can only be addressed through effective leadership and change management.
Phosphorylation of rat aquaporin‐4 at Ser111 is not required for channel gating

Aquaporin 4 (AQP4) is the predominant water channel in the mammalian brain and is mainly expressed in the perivascular glial endfeet at the brain‐blood interface. AQP4 has been described as an important entry and exit site for water during formation of brain edema and regulation of AQP4 is therefore of therapeutic interest. Phosphorylation of some aquaporins has been proposed to regulate their water permeability via gating of the channel itself. Protein kinase (PK)‐dependent phosphorylation of Ser111 has been reported to increase the water permeability of AQP4 expressed in an astrocytic cell line. This possibility was, however, questioned based on the crystal structure of the human AQP4. Our study aimed to resolve if Ser111 was indeed a site involved in phosphorylation‐mediated gating of AQP4. The water permeability of AQP4‐expressing Xenopus oocytes was not altered by a range of activators and inhibitors of PKG and PKA. Mutation of Ser111 to alanine or aspartate (to prevent or mimic phosphorylation) did not change the water permeability of AQP4. PKG activation had no effect on the water permeability of AQP4 in primary cultures of rat astrocytes. Molecular dynamics simulations of a phosphorylation of AQP4.Ser111 recorded no phosphorylation‐induced change in water permeability. A phospho‐specific antibody, exclusively recognizing AQP4 when phosphorylated on Ser111, failed to detect phosphorylation in cell lysate of rat brain stimulated by conditions proposed to induce phosphorylation of this residue. Thus, our data indicate a lack of phosphorylation of Ser111 and of phosphorylation‐dependent gating of AQP4.
Low Bandwidth Self-Healing Key Distribution for Broadcast Encryption

We introduce a new self-healing key distribution scheme with revocation capability. The main improvement that our proposed construction achieves over previously suggested self-healing key distribution schemes is that our self-healing technique reduces communication overhead from O(tj) to O(t+j) without any additional increment in the storage cost as compared to the earlier approaches, where j is the current session number and t is the maximum number of compromised group members that may collude. We provide rigorous treatment of security of our scheme in an appropriate security framework and show that it is unconditionally secure with forward and backward secrecy.
Interactive use of inductive approach for analyzing and developing conceptual structures

Inductive learning algorithms learns classification from training examples and uses induced classifier for dealing with new instances. The use of conceptual data structures for classifier's input is making this task more complicated and classifier may meet the difficulties in class prediction. To broaden applicability of inductive learning based classifiers a collaborative approach between the system and human expert would be useful. The proposed interactive system in uncertain conditions can ask for human advice and improve its knowledge base with the rule derived from this interaction. Interactive inductive learning based classification system is proposed for helping to compare university study courses semi-automatically.
Detecting speaker roles and topic changes in multiparty conversations using latent topic models

Accessing and browsing archives of multiparty conversations can be significantly facilitated by labeling them in terms of high level information. In this paper, we investigate automatic labeling of speaker roles and topic changes in professional meetings. Using the framework of unsupervised topic modeling we express speaker utterances as mixture of latent variables, each of which is governed by a multinomial distribution. The generated latent topic distributions are then used as features for predicting role and topic changes. Experiments performed on several hours of meeting data selected from AMI corpus reveal that latent topic features are effective predictors of speaker roles and topic changes. Furthermore, experiments also reveal an improvement in performance when latent topic information is combined with other multistream features. Index Terms: speaker role labeling, latent topic models, topic boundary detection
Genome-wide association study of survival in patients with pancreatic adenocarcinoma

Background and objective Survival of patients with pancreatic adenocarcinoma is limited and few prognostic factors are known. We conducted a two-stage genome-wide association study (GWAS) to identify germline variants associated with survival in patients with pancreatic adenocarcinoma. Methods We analysed overall survival in relation to single nucleotide polymorphisms (SNPs) among 1005 patients from two large GWAS datasets, PanScan I and ChinaPC. Cox proportional hazards regression was used in an additive genetic model with adjustment for age, sex, clinical stage and the top four principal components of population stratification. The first stage included 642 cases of European ancestry (PanScan), from which the top SNPs (p≤10−5) were advanced to a joint analysis with 363 additional patients from China (ChinaPC). Results In the first stage of cases of European descent, the top-ranked loci were at chromosomes 11p15.4, 18p11.21 and 1p36.13, tagged by rs12362504 (p=1.63×10−7), rs981621 (p=1.65×10−7) and rs16861827 (p=3.75×10−7), respectively. 131 SNPs with p≤10−5 were advanced to a joint analysis with cases from the ChinaPC study. In the joint analysis, the top-ranked SNP was rs10500715 (minor allele frequency, 0.37; p=1.72×10−7) on chromosome 11p15.4, which is intronic to the SET binding factor 2 (SBF2) gene. The HR (95% CI) for death was 0.74 (0.66 to 0.84) in PanScan I, 0.79 (0.65 to 0.97) in ChinaPC and 0.76 (0.68 to 0.84) in the joint analysis. Conclusions Germline genetic variation in the SBF2 locus was associated with overall survival in patients with pancreatic adenocarcinoma of European and Asian ancestry. This association should be investigated in additional large patient cohorts.
Relationship between Family Adaptability, Cohesion and Adolescent Problem Behaviors: Curvilinearity of Circumplex Model

Background The Family Adaptability and Cohesion Evaluation Scale (FACES) III using the circumplex model has been widely used in investigating family function. However, the criticism of the curvilinear hypothesis of the circumplex model has always been from an empirical point of view. This study examined the relationship between adolescent adaptability, cohesion, and adolescent problem behaviors, and especially testing the consistency of the curvilinear hypotheses with FACES III. Methods We used the data from 398 adolescent participants who were in middle school. A self-reported questionnaire was used to evaluate the FACES III and Youth Self Report. Results According to the level of family adaptability, significant differences were evident in internalizing problems (P = 0.014). But, in externalizing problems, the results were not significant (P = 0.305). Also, according to the level of family cohesion, significant differences were in internalizing problems (P = 0.002) and externalizing problems (P = 0.004). Conclusion The relationship between the dimensions of adaptability, cohesion and adolescent problem behaviors was not curvilinear. In other words, adolescents with high adaptability and high cohesion showed low problem behaviors.
Multilingual WSD-like Constraints for Paraphrase Extraction

The use of pivot languages and wordalignment techniques over bilingual corpora has proved an effective approach for extracting paraphrases of words and short phrases. However, inherent ambiguities in the pivot language(s) can lead to inadequate paraphrases. We propose a novel approach that is able to extract paraphrases by pivoting through multiple languages while discriminating word senses in the input language, i.e., the language to be paraphrased. Text in the input language is annotated with “senses” in the form of foreign phrases obtained from bilingual parallel data and automatic word-alignment. This approach shows 62% relative improvement over previous work in generating paraphrases that are judged both more accurate and more fluent.
Astrocyte-Originated ATP Protects Aβ1-42-Induced Impairment of Synaptic Plasticity

Activated microglia and reactive astrocytes are commonly found in and around the senile plaque, which is the central pathological hallmark of Alzheimer's disease. Astrocytes respond to neuronal activity through the release of gliotransmitters such as glutamate, d-serine, and ATP. However, it is largely unknown whether and how gliotransmitters affect neuronal functions. In this study, we explored the effect of a gliotransmitter, ATP, on neurons damaged by β-amyloid peptide (Aβ). We found that Aβ1-42 (Aβ42) increased the release of ATP in cultures of primary astrocytes and U373 astrocyte cell line. We also found that exogenous ATP protected Aβ42-mediated reduction in synaptic molecules, such as NMDA receptor 2A and PSD-95, through P2 purinergic receptors and prevented Aβ42-induced spine reduction in cultured primary hippocampal neurons. Moreover, ATP prevented Aβ42-induced impairment of long-term potentiation in acute hippocampal slices. Our findings suggest that Aβ-induced release of gliotransmitter ATP plays a protective role against Aβ42-mediated disruption of synaptic plasticity.
Next-Generation Sequencing: From Understanding Biology to Personalized Medicine

Within just a few years, the new methods for high-throughput next-generation sequencing have generated completely novel insights into the heritability and pathophysiology of human disease. In this review, we wish to highlight the benefits of the current state-of-the-art sequencing technologies for genetic and epigenetic research. We illustrate how these technologies help to constantly improve our understanding of genetic mechanisms in biological systems and summarize the progress made so far. This can be exemplified by the case of heritable heart muscle diseases, so-called cardiomyopathies. Here, next-generation sequencing is able to identify novel disease genes, and first clinical applications demonstrate the successful translation of this technology into personalized patient care.
Spurious fields in time-domain computations of scattering problems

Two-dimensional (2-D) electromagnetic scattering problems with a time-periodic incident field are considered. The scatterer is a perfect conductor, and an artificial boundary condition is used. The large-time behavior of solutions, depending on (divergence-free) initial conditions, is characterized. It turns out that in addition to the expected time-periodic solution, the limiting solution may also contain a spurious stationary field. The source of the stationary field is explained and equations describing it are obtained. Several avoidance strategies are discussed and numerical comparisons of these techniques are given.
A Comprehensive Study of Data Mining and Application

 Abstract— Data mining refers to extracting or ―mining‖ knowledge from large amounts of data. Data mining involves an integration of techniques from multiple disciplines such as database technology, statistics, machine learning, high performance computing, pattern recognition, neural networks, data visualization, information retrieval, image and signal processing, and spatial data analysis. Data mining applications can use a variety of parameters to examine the data. They include association, sequence or path analysis, classification, clustering and forecasting. An application compared to other data analysis applications such as structured queries or statistical analysis software. Illustration of the data mining application that offer opportunities for research. The overall goal of the data mining process is to extract information from a data set and transform it into an understandable structure for further use. In this paper present a comprehensive study for data mining, models, issue, and focuses its application.
Statistical Detection of Online Drifting Twitter Spam: Invited Paper

Spam has become a critical problem in online social networks. This paper focuses on Twitter spam detection. Recent research works focus on applying machine learning techniques for Twitter spam detection, which make use of the statistical features of tweets. We observe existing machine learning based detection methods suffer from the problem of Twitter spam drift, i.e., the statistical properties of spam tweets vary over time. To avoid this problem, an effective solution is to train one twitter spam classifier every day. However, it faces a challenge of the small number of imbalanced training data because labelling spam samples is time-consuming. This paper proposes a new method to address this challenge. The new method employs two new techniques, fuzzy-based redistribution and asymmetric sampling. We develop a fuzzy-based information decomposition technique to re-distribute the spam class and generate more spam samples. Moreover, an asymmetric sampling technique is proposed to re-balance the sizes of spam samples and non-spam samples in the training data. Finally, we apply the ensemble technique to combine the spam classifiers over two different training sets. A number of experiments are performed on a real-world 10-day ground-truth dataset to evaluate the new method. Experiments results show that the new method can significantly improve the detection performance for drifting Twitter spam.
Research on VLSI test compression

This paper explores the recent classic VLSI test compression methods, analyses the characteristics of each methods, make compression among them, the advantages and disadvantages of each proposed approaches are expounded. The main purpose for test compression is to reduce test application time, hardware overhead and test cost. The test compression solutions are mainly based on scan chain, and the X-filling methods are adopted for test compression. Finally this paper outlooks the prospective of VLSI test compression.
The Relationship Between Serum 25-Hydroxyvitamin D, Vitamin D and Calcium Intake, and Adiposity in Infants

THE RELATIONSHIP BETWEEN SERUM 25-HYDROXYVITAMIN D, VITAMIN D AND CALCIUM INTAKE, AND ADIPOSITY IN INFANTS by Carolyn W. Morris Purpose: National prevalence of childhood overweight and obesity has plateaued in recent years, but rates remain high, with approximately 10% among children 2 hours). Anthropometric measures and bloodwork for serum 25(OH)D were obtained during at the time of the study visit. Weight-for-length (WFL) percentile status was determined using WHO growth standards (low weight 97.7 %ile) and WFL z-scores were calculated. ANOVA was used to compare mean serum 25(OH)D and calcium and vitamin D intake by WFL status. Chi square analysis was used to evaluate the relationship between serum 25(OH) D status (deficient = 20 ng/mL), calcium intake status (sufficient = >700 mg), vitamin D intake status (sufficient = >400 IU) and WFL percentile status. Pearson’s correlation coefficient was used to assess the strength and significance of associations between serum 25(OH)D, calcium and vitamin D intake and WFL z-score. The analysis was repeated after subdivision by race and sun exposure. Results: 125 infants and toddlers (9 to 24 months of age, 68% African American) participated in the study. Approximately 11% of the population had a high weight. Mean vitamin D intake (~600 IU/d) and median calcium intake (~1550 mg/d) exceeded recommendations. Prevalence of high weight was higher among children with adequate intake compared to those who consumed less than the recommendations (calcium: 41% vs. 36%, respectively; vitamin D: 45% vs. 29%, respectively). However, this difference was not statistically significant. Mean serum 25(OH)D level (37 ng/mL) was sufficient. When compared across WFL status, neither mean serum 25(OH)D nor mean intake of calcium and vitamin D varied significantly. No significant correlation was found between WFL and serum 25(OH)D for the cohort or any of the subgroups examined. Conclusions: Rates of infant overweight and obesity in our sample are similar in comparison with the national average. Our results do not support a relationship between calcium and vitamin D intake on weight status or an association between serum vitamin D and body composition in children of this age. Future studies are needed to re-examine these relationships in a larger group of children of more evenly distributed weight status. THE RELATIONSHIP BETWEEN SERUM 25-HYDROXYVITAMIN D, VITAMIN D AND CALCIUM INTAKE, AND ADIPOSITY IN INFANTS
Accurate Corner Detection using 4-directional Edge Labeling and Corner Positioning Templates

Corner positioning templates are proposed in order to detect the accurate positions of corners that are extracted using 4-directional edge labeling. Top-down and bottom-up directional labeling are used to label the edge segments with four kinds of labels according to their directions. The points whose labels have changed are then determined as corners. The exact positions of the missing corners due to the disconnected edges are detected through the corner positioning templates that are determined according to the labels of start-points and end-points after the two-pass edge labeling. Experiment results show that the proposed method can detect the exact positions of the real corners.
A Scalable Clustering Technique for Intrusion Signature Recognition

-- This paper presents a data mining algorithm, namely Clustering and Classification Algorithm – Supervised (CCA-S), which we developed for detecting intrusions into computer network systems for intrusion detection. CCA-S is used to learn signature patterns of both normal and intrusive activities in the training data, and to classify the activities in the testing data as normal or intrusive based on the learned signature patterns of normal and intrusive activities. CCA-S differs from many existing data mining techniques in its ability in scalable, incremental learning. We tested CCA-S and two popular decision tree algorithms
Behavioural and endocrine predictors of dominance and tolerance in female common marmosets,
 Callithrix jacchus
 


Abstract As a result of social subordination, female common marmosets undergo suppression of ovulation and inhibition of sexual behaviour. This study examined the possibility that subordination also results in decreased aggressiveness and increased submissiveness towards same-sex strangers. Thirty-two adult females were pre-assigned to eight mixed-sex social groups. The females' behavioural and adrenocortical responses to brief confrontations with each of three female strangers were assessed under two conditions: while subjects were pair-housed with a male and while they were living in established, mixed-sex groups. Only 22% of subjects threatened stimulus females in the heterosexual pairs condition, 47% submitted and 31% showed no agonism. These agonistic behaviour patterns reliably predicted whether a female would become dominant or subordinate in a mixed-sex group. When animals were housed in established social groups, both dominant and subordinate females either showed similar responses to stimulus animals as they did in the earlier condition or became somewhat less responsive. Plasma cortisol levels did not correlate with agonistic behaviour and were not elevated by stranger-encounter testing. Finally, in the first 10 days following group formation, subordinate females that had shown ovulatory cyclicity prior to group formation were significantly more likely to receive persistent aggression from their dominant female groupmate than subordinates that had been anovulatory. These results suggest that attainment of social status between female marmosets is closely related to pre-existing individual differences in agonistic behaviour, whereas tolerance between females depends upon ovarian function.
Cortical areas mediating stereopsis in the human brain: a PET study

Using PET, we investigated the neural substrates of stereodepth perception in humans. The presentation of Julesz-type random-dot stereograms (RDS) produced significant rCBF elevations in Brodmann areas (BA) 18, 19 and 7, all in the right hemisphere. Activation foci were also found in both middle temporal areas (MT). These results demonstrate that, as in primates, cortical area MT and extrastriate areas are central to stereovision and that a network of predominant right hemispheric regions is recruited to meet visuo-spatial processing demands associated with horizontal binocular disparity inputs.