Miracle-dz/UniFAR-FTUs huggingface dataset:
Transcriptome Analysis of the Hippocampal CA1 Pyramidal Cell Region after Kainic Acid-Induced Status Epilepticus in Juvenile Rats

Molecular mechanisms involved in epileptogenesis in the developing brain remain poorly understood. The gene array approach could reveal some of the factors involved by allowing the identification of a broad scale of genes altered by seizures. In this study we used microarray analysis to reveal the gene expression profile of the laser microdissected hippocampal CA1 subregion one week after kainic acid (KA)-induced status epilepticus (SE) in 21-day-old rats, which are developmentally roughly comparable to juvenile children. The gene expression analysis with the Chipster software generated a total of 1592 differently expressed genes in the CA1 subregion of KA-treated rats compared to control rats. The KEGG database revealed that the identified genes were involved in pathways such as oxidative phosporylation (26 genes changed), and long-term potentiation (LTP; 18 genes changed). Also genes involved in Ca2+ homeostasis, gliosis, inflammation, and GABAergic transmission were altered. To validate the microarray results we further examined the protein expression for a subset of selected genes, glial fibrillary protein (GFAP), apolipoprotein E (apo E), cannabinoid type 1 receptor (CB1), Purkinje cell protein 4 (PEP-19), and interleukin 8 receptor (CXCR1), with immunohistochemistry, which confirmed the transcriptome results. Our results showed that SE resulted in no obvious CA1 neuronal loss, and alterations in the expression pattern of several genes during the early epileptogenic phase were comparable to previous gene expression studies of the adult hippocampus of both experimental epileptic animals and patients with temporal lobe epilepsy (TLE). However, some changes seem to occur after SE specifically in the juvenile rat hippocampus. Insight of the SE-induced alterations in gene expression and their related pathways could give us hints for the development of new target-specific antiepileptic drugs that interfere with the progression of the disease in the juvenile age group.
Performance Comparison of OLSR with ETX_Float and ETX_ff in a MANET Testbed

Recently, Mobile Ad-hoc Networks (MANETs) have an increased interest in applications for covering rural areas due to the possibility of usage of low-cost and high-performance mobile terminals, without having to depend on the network infrastructure. Because the terminals are mobile, the routes change dynamically, so routing algorithms are an important issue for operation of MANETs. In this paper, we investigate the behaviour of OLSR Routing Protocol for different ETX algorithms. We conduct experiments in a MANET testbed. We consider different HELLO packets interval of OLSR and compare ETX_ff and ETX_float link quality metrics. We design and implement two experimental scenarios in our academic environment and investigate their performance behaviour for different number of hops.
The Best of BothWorlds: Combining Data-Independent and Data-Driven Approaches for Action Recognition

Motivated by the success of CNNs in object recognition on images, researchers are striving to develop CNN equivalents for learning video features. However, learning video features globally has proven to be quite a challenge due to the difficulty of getting enough labels, processing large-scale video data, and representing motion information. Therefore, we propose to leverage effective techniques from both data-driven and data-independent approaches to improve action recognition system. Our contribution is three-fold. First, we explicitly show that local handcrafted features and CNNs share the same convolution-pooling network structure. Second, we propose to use independent subspace analysis (ISA) to learn descriptors for state-of-the-art handcrafted features. Third, we enhance ISA with two new improvements, which make our learned descriptors significantly outperform the handcrafted ones. Experimental results on standard action recognition benchmarks show competitive performance.
Use of Discourse Markers in Writing and Answering Essay Questions among Undergraduates in Ondo State University of Science and Technology, Okitipupa, Nigeria

The study examined the students’ level of mastery of discourse markers in writing and answering essay questions. It also determined the likely barriers to effective use of discourse markers and established the different strategies in teaching discourse markers (DMs). This was to promote effective learning of discourse markers and their correct use in writing and answering essay questions. The study adopted the survey research design. The population consisted of all the undergraduate students of Ondo State University of Science and Technology, Okitipupa. An intact sampling technique was employed in selecting all first semester Part 1 students of 2013/2014 academic session comprising 265 students across all the four Departments in the Faculty of Science of the University. An instrument tagged: “GST 101 Examination Question” was developed by the investigator. This consisted of four sections of different items which were used to collect data from the respondents. Two research questions and two hypotheses emanated from the study. Data collected were analysed using frequency count, simple percentage, and ANCOVA. The findings among others, showed that 141(53.2%) of the respondents had low understanding of discourse markers such as: in addition, followed by linkers showing relationship with 137(51.2%). The results further showed that 231(87.2%), representing majority of the respondents were of the view that lack of mastery of the various connectors is a major barrier to effective writing and answering of essay questions. The results also affirmed that there is significant difference in students’ academic performance in using discourse markers in writing and answering essay questions across different Departments (F=11.345) p<0.05). The study concluded that students need to be properly taught to master the various discourse markers for effective writing and answering essay questions. https://doi.org/10.26803/ijlter.17.7. 7
Aes Security Report Executive Summary Resistance to Statistical Attacks 1.1 Linear and Differential Attacks on Aes 1.2 More General Statistical Models for Block Ciphers

Project co-funded by the European Commission within the 6th Framework Programme Dissemination Level PU Public X PP Restricted to other programme participants (including the Commission services) RE Restricted to a group specified by the consortium (including the Commission services) CO Confidential, only for members of the consortium (including the Commission services) The information in this document is provided as is, and no warranty is given or implied that the information is fit for any particular purpose. The user thereof uses the information at its sole risk and liability. In October 2000, NIST announced the selection of Rijndael, a symmetric cipher proposed by Joan Daemen and Vincent Rijmen, as the Advanced Encryption Standard (AES). AES was published as a FIPS standard in November 2001 [101], and is gradually becoming one of the most widely used block ciphers worldwide. This report was prepared by a group of cryptography experts from industry and academia, as part of the joint research achieved within the Symmetric Techniques Virtual Laboratory (STVL) of the European project ECRYPT. It was motivated by the fact that since the selection of the AES five years ago, there have been a variety of research results leading to speculation about the long-term security of the cipher. Thus the purpose of this report is to provide an update on the recent advances in various aspects of the analysis of AES and to assess their impact upon the practical security of the cipher. In order to minimize overlap with the content of former reports on the security of AES, namely the one published in 2000 by NIST [73] and the one published in February 2003 by the European project NESSIE [102], this report only provides a very short account of results already mentioned in these reviews and mainly focuses on more recent security results. Comprehensive surveys of design and implementation aspects of AES are available in the author's book " The Design of Rijndael " [52] and on the AES lounge maintained by the Crypto group of the Technology University of Graz [72]. The following aspects of the AES security are investigated in this report: • Resistance to statistical attacks (Chapter 1); • Resistance to attacks exploiting multiset properties (Chapter 2); • Resistance to algebraic attacks (Chapter 3); • Resistance to generic trade off attacks (Chapter 4); • Special properties not directly related to potential attacks (Chapter 5); • Potential vulnerability of AES implementations …
Adoption leadership and early planners: Comcast's IP upgrade strategy

Diffusion of innovation literature categorizes new technology adopters into five groups.9 Leaders and early adopters are typified by low aversion to risk while laggards and late adopters are characterized by cautiousness. Occasionally self-described laggards behave as early adopters. In this article, we examine the early implementation by a late adopter in a semi-crisis position, using the case of Comcast IPv6 adoption as an example. Comcast faced an unexpected resource crisis by exhausting the private IP address space they use for their networking infrastructure management. Without ambitions of an early adopter, Comcast considered IPv6 when analyzing the best solutions to their problem. This decision positioned Comcast in an adoption leadership role while enabling the company to overcome the risks associated with early adoption. Consequently, Comcast is leveraging its adoption leadership to gain competitive advantage in the cable industry and global brand-name recognition. Comcast’s adoption case also introduces a new phenomenon in the adoption of complex technology – the early planner. Early planners begin their adoption plans in tandem with adoption leaders, but often wait for implementation until the technology is more mature. IPv6 was first introduced in 1995 by the Internet Engineering Task Force with the main objective of overcoming the address size limitations of IPv4. Until recently IPv6 has not been widely adopted partially due to the deployment of supplemental technologies that temporarily slowed down the IPv4 address space depletion. These band-aid solutions led to loss of interest and lack of compelling business value in the implementation of the new standard. IPv6 has several intrinsically unique characteristics that moderate its adoption prospects. IPv6 is an infrastructure technology, hidden from the end-user. Companies in non-IT related industries (such as, services, finance) are unlikely to see its immediate benefits. In addition, managers are often reluctant to adopt new infrastructure technologies fearing interference with the quality of the services they provide customers. In a survey conducted by Cisco, 64% of the respondents stated they fear that implementing IPv6 will impact the continuity of their daily operations. Often, companies that define themselves as early adopters of new services lag in the adoption of new infrastructure technologies. Unlike most new technologies, IPv6 was not developed by a commercial entity. Rather, it was developed by a non-profit, distributed organization. adoption Leadership and early planners: comcast’s ip upgrade strategy
From Early Sensory Specialization to Later Perceptual Generalization: Dynamic Temporal Progression in Perceiving Individual Threats

Threat evokes a variety of negative emotions such as fear, anger, and disgust. Whereas they elicit distinct and even opposite facial, sensory, and autonomic reflexes, threat-related emotions often converge in the actions they prompt (e.g., negative evaluation and avoidance). Here, we tested a unifying hypothesis that threat processing initially involves specialized encoding of individual subtypes to support discrete reflexive operations that later gives way to generalized elaborate analysis to facilitate convergent defensive behavior. Combining event-related potentials (ERPs) and a defensive context in human subjects, we compared temporal courses of perceptual analysis of two threat subtypes—fear and disgust. Indeed, fear enhanced and disgust suppressed early (115 ms) response in visual cortex, accentuating specialized sensory encoding of threat subtypes in accordance with the opposite behavioral and autonomic reflexes they typically elicit. By contrast, later ERP waveforms evoked by fear and disgust merged gradually over time (130–425 ms). Consistently, visual ERPs to anthropomorphic Greeble objects presented after fear versus disgust images also overlapped despite their clear departure from the neutral condition, paralleled by comparable exaggeration in Greeble imminence perception in the two threat (vs neutral) conditions. This later confluence of neural and behavioral response between fear and disgust thus highlights general threat categorization in high-level, downstream perception of threat. By delineating the temporal dynamics in perceiving individual threat emotions, our findings thus provide some of the first evidence to reconcile multidimensional and unidimensional aspects of information processing within the domain of threat, shedding new light on symptom heterogeneity across the anxiety disorder spectrum.
LETOR : A Benchmark Collection LETOR : A Benchmark Collection for Learning to Rank for Information Retrieval by Microsoft Research Asia , an incomplete draft

Learning to rank has attracted great attention recently in both information retrieval and machine learning communities. However, the lack of public dataset had stood in its way until the LETOR benchmark dataset (actually a group of three datasets) was released in the SIGIR 2007 workshop on Learning to Rank for Information Retrieval (LR4IR 2007). Since then, this dataset has been widely used in many learning to rank papers, and has greatly speeded up the corresponding research. Recently, we released the latest version, LETOR3.0. LETOR3.0 makes a lot of improvement over previous two versions, and it is more useful and reliable. In this paper, we describe the details of datasets in LETOR3.0, including collection information, query sets and implementation of feature extraction. We also benchmark several widely used learning to rank methods on LETOR3.0, illustrating the results of these methods, suggesting new directions for research, and providing baseline results for future study.
Mixed Methods Study of Multiple High-Risk Behavior Prevention Program on High School Students

Crystal Collier, Jessica Davison, and Anthony J. Onwuegbuzie aThe Council on Recovery, TX, USA and Department of Educational Leadership and Counseling, Sam Houston State University, TX, USA; bThe Council on Recovery, TX, USA; cDepartment of Educational Leadership, Sam Houston State University, TX, USA and Department of Educational Leadership and Management/Department of Educational Psychology, University of Johannesburg, Johannesburg, South Africa
Gastrointestinal-Sparing Effects of Novel NSAIDs in Rats with Compromised Mucosal Defence

Nonsteroidal anti-inflammatory drugs are among the most commonly used prescription and over-the-counter medications, but they often produce significant gastrointestinal ulceration and bleeding, particularly in elderly patients and patients with certain co-morbidities. Novel anti-inflammatory drugs are seldom tested in animal models that mimic the high risk human users, leading to an underestimate of the true toxicity of the drugs. In the present study we examined the effects of two novel NSAIDs and two commonly used NSAIDs in models in which mucosal defence was expected to be impaired. Naproxen, celecoxib, ATB-346 (a hydrogen sulfide- and naproxen-releasing compound) and NCX 429 (a nitric oxide- and naproxen-releasing compound) were evaluated in healthy, arthritic, obese, and hypertensive rats and in rats of advanced age (19 months) and rats co-administered low-dose aspirin and/or omeprazole. In all models except hypertension, greater gastric and/or intestinal damage was observed when naproxen was administered in these models than in healthy rats. Celecoxib-induced damage was significantly increased when co-administered with low-dose aspirin and/or omeprazole. In contrast, ATB-346 and NCX 429, when tested at doses that were as effective as naproxen and celecoxib in reducing inflammation and inhibiting cyclooxygenase activity, did not produce significant gastric or intestinal damage in any of the models. These results demonstrate that animal models of human co-morbidities display the same increased susceptibility to NSAID-induced gastrointestinal damage as observed in humans. Moreover, two novel NSAIDs that release mediators of mucosal defence (hydrogen sulfide and nitric oxide) do not induce significant gastrointestinal damage in these models of impaired mucosal defence.
Investigation of Relationship Between Rainfall and Vegetation Index by Using NOAA/AVHRR Satellite Images

Use of satellite images is known as a new technique to study changes in vegetation cover. On the other hand, rainfall plays a key role on the condition of vegetation cover. This article investigates the changes in vegetation and its relation to rainfall days and monthly time intervals over the (2000-2003) period. The region of study is part of Azerbaijan province located in an area surrounded. Using geo-statistical methods, rainfall maps were generated based on the rain gauges in the data collected by area. Maps of daily Normalized Difference Vegetation index (NDVI) were transformed days images using into day composite technique. By maximum preparing a layer representing terrain-mapping units (TMU), the correlation between vegetation cover and rainfall was investigated in different land units. The results demonstrate varying degree of correlation. Specifically, the correlation in alluvial and flood plains was strongest. Meanwhile, the correlation in monthly time days interval was better compares to interval. The multi-variable regression was also determined as the most suited correlation relationship.
Turbulent diffusion in protoplanetary discs: the effect of an imposed magnetic field

We study the effect of an imposed vertical magnetic field on the turbulent mass diffusion properties of magnetorotational turbulence in protoplanetary discs. It is well-known that the effective viscosity generated by the turbulence depends strongly on the magnitude of such an external field. In this Letter we show that the turbulent diffusion of the flow also changes, but that the diffusion coefficient does not rise with increasing vertical field as fast as the viscosity does. The vertical Schmidt number, i.e. the ratio between viscosity and vertical diffusion, can be close to 20 for high field magnitudes, whereas the radial Schmidt number is increased from below unity to around 3.5. Our results may have consequences for the interpretation of observations of dust in protoplanetary discs and for chemical evolution modelling of these discs.
A Primer for Using and Understanding Weights With National Datasets

Using data from the National Study of Postsecondary Faculty and the Early Childhood Longitudinal Study—Kindergarten Class of 1998-99, the author provides guidelines for incorporating weights and design effects in single-level analysis using Windows-based SPSS and AM software. Examples of analyses that do and do not employ weights and design effects are also provided to illuminate the differential results of key parameter estimates and standard errors using varying degrees of using or not using the weighting and design effect continuum. The author gives recommendations on the most appropriate weighting options, with specific reference to employing a strategy to accommodate both oversampled groups and cluster sampling (i.e., using weights and design effects) that leads to the most accurate parameter estimates and the decreased potential of committing a Type I error. However, using a design effect adjusted weight in SPSS may produce underestimated standard errors when compared with accurate estimates produced by specialized software such as AM.
Evaluating L1CAM expression in human endometrial cancer using qRT-PCR

Background Management of endometrial carcinoma (EC) still needs improvement of risk assessment. Recently, L1CAM immunohistochemical (IHC) evaluation showed a unique value to predict the outcome of early EC. However IHC results are often conflicting for lack of inter-laboratory standardisation. Methods Here, as a proof of concept and to increase reproducibility we assayed eighty-two EC and 26 normal endometrium samples for L1CAM expression (L1CAMEXP) via qRT-PCR. The IHC evaluation was performed in 50 cancer samples. Moreover, we aimed to substantiate the in-vitro findings of L1CAM regulation through its promoter methylation (L1CAMMET), miR-34a expression and miR-34a promoter methylation. DNA methylation was assessed with MethyLight PCR technique. Results High overall concordant results between IHC and RT-PCR evaluations were found. L1CAMEXP was detected in 11% of cancer specimens. These positive cancers exhibited a worse DFS (p=0.032) and OS (p=0.016) in a multivariate COX-regression model. L1CAMEXP predicted distant failure (p=0.007) and L1CAMMET predicted risk-reduction of lymph-node involvement (p=0.005). Inverse correlations between L1CAMEXP and L1CAMMET (p=0.004) and between L1CAMEXP and miR-34a expression (p=0.002) were found. Conclusions In conclusion qRT-PCR analysis is a reliable approach to evaluate L1CAM status in EC and L1CAMEXP was highly predictive for distant failure and poor outcome, confirming the large IHC-based studies. Interestingly, L1CAMMET was able to assess the risk of pelvic lymph-node involvement. Especially the latter finding has to be confirmed in larger prospective series.
Developing a Deep Linguistic Databank Supporting a Collection of Treebanks: the CINTIL DeepGramBank

Corpora of sentences annotated with grammatical information have been deployed by extending the basic lexical and morphological data with increasingly complex information, such as phrase constituency, syntactic functions, semantic roles, etc. As these corpora grow in size and the linguistic information to be encoded reaches higher levels of sophistication, the utilization of annotation tools and, above all, supporting computational grammars appear no longer as a matter of convenience but of necessity. In this paper, we report on the design features, the development conditions and the methodological options of a deep linguistic databank, the CINTIL DeepGramBank. In this corpus, sentences are annotated with fully fledged linguistically informed grammatical representations that are produced by a deep linguistic processing grammar, thus consistently integrating morphological, syntactic and semantic information. We also report on how such corpus permits to straightforwardly obtain a whole range of past generation annotated corpora (POS, NER and morphology), current generation treebanks (constituency treebanks, dependency banks, propbanks) and next generation databanks (logical form banks) simply by means of a very residual selection/extraction effort to get the appropriate ""views"" exposing the relevant layers of information.