Miracle-dz/UniFAR-FTUs huggingface dataset:
CEST: City Event Summarization using Twitter

Twitter, with 288 million active users, has become the most popular platform for continuous real-time discussions. This leads to huge amounts of information related to the real-world, which has attracted researchers from both academia and industry. Event detection on Twitter has gained attention as one of the most popular domains of interest within the research community. Unfortunately, existing event detection methodologies have yet to fully explore Twitter metadata and instead rely solely on identifying events based on prior information or focus on events that belong to specific categories. Given the heavy volume of tweets that discuss events, summarization techniques can be used to create overviews that capture key facts related to events. Unfortunately, these techniques are constrained to analyze only well-structured events. In this project, we conducted an in-depth study on the usage of Twitter around Points-of-Interest to verify that indeed Twitter data can be used to detect events of a city. Thereafter, we designed and implemented CEST (City Event Summarization using Twitter), a tool that analyzes tweets to identify different types of events occurring in a city and generate the corresponding summaries for the detected events. Unlike existing methodologies, we developed CEST to process unstructured documents and take advantage of short hand notations, hashtags, keywords, geographical data, temporal information, and sentiment terms within tweets in-tandem to both detect and generate a brief overview of events without prior knowledge. Furthermore, we vi introduced a novel strategy that analyzes sentiment and tweeting behavior of users over time to create a qualitative score that captures events’ appeal to attendees.
Long Noncoding RNAs in Pathological Cardiac Remodeling: A Review of the Update Literature

Cardiac remodeling is a self-regulatory response of the myocardium and vasculature under the stressful condition. Cardiomyocytes (CMs), vascular smooth muscle cells (VSMCs), endothelial cells (ECs), and cardiac fibroblasts (CFs) are all involved in this process, characterized by change of morphological structures and mechanical/chemical activities as well as metabolic patterns. Despite current development of consciousness, the control of cardiac remodeling remains unsatisfactory, and to further explore the underlying mechanism and seek the optimal therapeutic targets is still the urgent need in clinical practice. It is now emerging that long noncoding RNAs (lncRNAs) play key regulatory roles in these adverse responses: lncRNA TUG1, AK098656, TRPV1, GAS5, Giver, and Lnc-Ang362 have been indicated in hypertension-related vascular remodeling, H19, TUG1, UCA1, MEG3, APPAT, and lincRNA-p21 in atherosclerosis (AS), and HIF1A-AS1 and Lnc-HLTF-5 in aortic aneurysm (AA). In addition, Neat1, AK139328, APF, CAIF, AK088388, CARL, MALAT1, HOTAIR, XIST, and NRF are involved in postischemia myocardial remodeling, while Mhrt, Chast, CHRF, ROR, H19, Plscr4, and MIAT are involved in myocardial hypertrophy, and MALAT1, wisper, MEG3, and H19 are involved in extracellular matrix (ECM) reconstitution. Signaling to specific miRNAs by acting as endogenous sponge (ceRNA) was the main form that regulates the target gene expression during cardiac remodeling. This review will underline the updates of lncRNAs and lncRNA-miRNA interactions in maladaptive remodeling and also cast light on their potential roles as therapeutic targets, hoping to provide supportive background for following research.
Fairness-Efficiency Allocation of CPU-GPU Heterogeneous Resources

Considering the performance improvement the cloud technology provides by processing workloads in parallel, applications and services are now migrating to online clouds. In a cloud platform, workloads can be executed in a virtualized environment to have a great improvement of the resource utilization. However, there is a new challenge in the allocation problem, which is quantifying and optimizing the fairness and efficiency of heterogeneous resources (CPUs and GPUs) required by applications such as cloud gaming. The solving approach needs scalarization methods of the requirement vector, relevant functions for fairness metrics, and an acceptable algorithm to solve that, where the difficulties mainly locate. We design an iterative, dynamic-adaptive heuristic solving algorithm Fairness-Efficiency Allocation (FEA) and optimize the implementation on a virtualized platform, which collects runtime data, allocates resources and reports differences. Data are recorded and analyzed to discover the effect of the allocation in different situations, including the promotion of fairness and the effect on the frame rate of the workloads. The result indicates that there is a considerable fairness improvement after the resource allocation, especially in situations that many virtual machines are executing simultaneously. Compared with the VGASA strategy, the fairness metric value improved 45 percent in three virtual machines’ situation.
Genetic Gain for Yield and Allelic Diversity over 35 Years of Durum Wheat Breeding at ICARDA

The ICARDA’s durum wheat breeding program was established in 1977 in Aleppo, Syria, where it continued its work targeted to the drylands of the developing world until 2012, when it was forced to relocate. This movement represented an occasion to measure the impact of 35 years of public breeding via a detailed genetic gain (GG) study. A total of 22 ICARDA’s historical entries representing three decades of work (1974–1984, 1985–1994, or 1995–2004), were placed in competition with elites from the most recent decade (2005–2011). A total of 10 environments and 7 sites were used for the assessment. Decade-wise GG for grain yield was measured to reveal >9% (equal 0.9% per year) at 8 of the environments, while no progress was found for the dry and cold conditions of the Atlas Mountains. Combined analysis revealed an average GG per year of 0.7%, mostly driven by earlier flowering and an increase in spike density. The germplasm was also characterized with 60 polymorphic SNPs to reveal that the breeding process has already eroded 6.3% of the original genetic diversity, and that over 3-folds reduction has occurred for rare alleles. Clustering analysis confirmed that two sub-populations have substantially disappeared under the breeding selection pressure. The results presented here show that good progress was made till now, but at the cost of reducing genetic diversity and pushing toward very early genotypes. A revamped strategy is then needed to continue delivering germplasm that is meaningful to breeders worldwide.
Optimization of gray model of the passenger flux forecast during the spring festival

According to the analysis of the passenger flux data, the railway station is taken as an essential gray system. Therefore, the gray forecast method is used to predict the passenger flux during the spring festival. Several measures are used to optimize the basal forecast model, such as choosing the optimized parameter in the error-corrected model, using new information model etc. The actual data indicate that the forecasting result is reliable.
Dynamic Web Caching Services of Different Java Application in e - Governance : Case Study

In this paper we will discuss that to day's the most popular web sites are suffering from the server congestion, and they are getting thousands of requests every second from the client. The heterogeneity and complexity of services and applications provided by web server systems is continuously increasing. Traditional web publishing sites with most static contents have being integrated with recent web commerce and transactional sites combining as dynamic and secure by services. The most understandable way to cope with growing service demand and application complexity is adding hardware resources because replacing an existing machine with a faster model provides only temporary relief from server overload. The need to optimize the performance of Web services is producing a variety of novel architec tures. (Rajeev Kumar, M.K. Sharma. Dynamic Web Caching Services of Different Java Application in e - Governance: Case Study. Academia Arena 2013;5(4):28 - 29 ) (ISSN 1553 - 992X). http://www.sciencepub. net/academ ia . 4
Effects of human-induced disturbances and weather on herbivore movement

Human-caused habitat disturbances and climate change are leading threats to biodiversity. Studying the impacts of human activities on wildlife from a behavioral perspective is a relevant starting point to understand the mechanisms underlying population and species resistance and resilience to disturbances. In this study, we assessed the effects of weather (temperature and precipitation), habitat disturbances (roads and clearcuts), and natural habitat types on the space use patterns of a threatened boreal population of woodland caribou (Rangifer tarandus caribou). An extensive data set of 288,665 relocations from 50 adult females outfitted with GPS collars over 7 years in the boreal forest of Québec, Canada was used to evaluate residency time in natural and disturbed habitats for five distinct biologically defined periods. The most parsimonious linear mixed-effects model for each period showed that individuals stayed longer in more natural habitat types. During calving and summer, residency time decreased with increasing road density, whereas residency time decreased with increasing temperature during winter and spring. We found no evidence of a synergistic effect between daily weather and human disturbances on movement behavior of caribou, but consider their respective influence as additive. We also showed large individual variation in residency time, except during the calving period. Lower individual variation in residency time during calving may be explained by strong evolutionary constraints on behavior faced by females to ensure protection and survival of their offspring. Based on our results, we suggest keeping large patches of suitable and roadless habitat for caribou to favor the spacing-out antipredator strategy exhibited by females during calving. By tracking individuals over several complete annual cycles, we showed variation in the effects of daily weather and human disturbances on residency time across biological periods. Our study highlights that the inclusion of daily weather variables helps better understand space-use patterns of a threatened species.
Synergistic interplay between PHF8 and HER2 signaling contributes to breast cancer development and drug resistance

HER2 plays a critical role in tumorigenesis and is associated with poor prognosis of HER2-positive breast cancers. Although, anti-HER2 drugs show benefits in breast cancer therapy, de novo or acquired resistance often develop. Epigenetic factors have been increasingly targeted for therapeutic purposes, however, such mechanisms interacting with HER2 signaling are poorly understood. This study reports the synergistic interplay between histone demethylase PHF8 and HER2 signaling, i.e. PHF8 is elevated in HER2-positive breast cancers and is upregulated by HER2; PHF8 plays coactivator roles in regulating HER2 expression and HER2-driven epithelial-to-mesenchymal transition (EMT) markers and cytokines. The HER2-PHF8-IL-6 regulatory axis was proved both in cell lines and in the newly established MMTV-Her2/MMTV-Cre/Phf8flox/flox models, with which the oncogenic function of Phf8 in breast cancer in vivo was revealed for the first time. Furthermore, PHF8-IL-6 axis contributes to the resistance of Trastuzumab in vitro and may play a critical role in the infiltration of T-cells in HER2-driven breast cancers. This study reveals novel epigenetic mechanisms underlying HER2-driven cancer development and anti-HER2 drug resistance.
Is catchment geodiversity a useful surrogate of aquatic plant species richness?

Conserving freshwater biodiversity in a rapidly changing world requires updated planning schemes and research efforts. Geodiversity – the diversity of Earth surface forms, materials and processes – and biodiversity are interlinked at a fundamental level. This relationship is being considered in a growing number of studies, yet research from freshwater environments is scarce. We used geodiversity (rock‐type, soil‐type and geomorphological richness), local and climatic variables to explore whether geodiversity can be used as a surrogate for aquatic plant species richness in lakes and rivers.
Critical brain dynamics and human intelligence

According to the critical brain hypothesis, the brain is considered to operate near criticality and realize efficient neural computations. Despite the prior theoretical and empirical evidence in favor of the hypothesis, no direct link has been provided between human cognitive performance and the neural criticality. Here we provide such a key link by analyzing resting-state dynamics of functional magnetic resonance imaging (fMRI) networks at a whole-brain level. We develop a novel data-driven analysis method, inspired from statistical physics theory of spin systems, to map out the whole-brain neural dynamics onto a phase diagram. Using this tool, we show evidence that dynamics of more intelligent human participants are closer to a critical state, i.e., the boundary between the paramagnetic phase and the spin-glass (SG) phase. This result was specific to fluid intelligence as opposed to crystalized intelligence. The present results are also consistent with the notion of “edge-of-chaos” neural computation. Author summary According to the critical brain hypothesis, the brain should be operating near criticality, i.e., a boundary between different states showing qualitatively different dynamical behaviors. Such a critical brain dynamics has been considered to realize efficient neural computations. Here we provide direct neural evidence in favor of this hypothesis by showing that the brain dynamics in more intelligent individuals are closer to the criticality. We reached this conclusion by deploying a novel data-analysis method based on statistical-physics theory of Ising spin systems to functional magnetic resonance imaging (fMRI) data obtained from human participants. Specifically, our method maps multivariate fMRI data obtained from each participant to a point in a phase diagram akin to that of the Sherrington-Kirkpatrick model of spin-glass systems. The brain dynamics for the participants having high fluid intelligence scores tended to be close to the phase boundary, which marks criticality, between the paramagnetic phase and the spin-glass phase, but not to the boundary between the paramagnetic and ferromagnetic phases.
Semantic polarity analysis and opinion mining on Chinese review sentences

By using natural language management technology, Chinese Web review sentences were semantic studied and opinion mined. A new algorithm for computing the contextual polarity of polar words was proposed, and a framework was introduced for topic identification and feature extraction. The framework provided an innovative solution for the association of extracted opinion to its specific topic. The experiment results show that the algorithm is both reasonable and effective compared with the results of manual annotation.
Research on super-resolution image reconstruction

Super-resolution image reconstruction is a technique to reconstruct high resolution image or video from a sequence of low resolution images.It has been widely used in digital TV,medicinal processing,military and remote sensing.The super resolution method is summarized in this paper.Some super resolution image reconstructions are discussed for super-resolution image reconstruction.The tendency and development prospect are also discussed.
Strategy Used to Solve Coverage Problem in Wireless Sensor Network

The study of Wireless sensor network is challenging in that it requires an enormous breadth of knowledge form. They are rapidly growing area for research and commercial deployment. Wireless sensor networks address a broad range of applications related to heathcare, industrial, area , surveillance and environmental monitoring. One of the most active research area in wireless sensor network is that of coverage.This paper presents effective coverage strategy for wireless sensor network. This mainly focus on two coverage strategies which are compared. In this paper we compare Delaunay triangulation and square grid coverage strategy on different parameters. Keywords-coverage problems, delaunay triangulation, sensor nodes,square grid,wireless sensor networks.
Beijing and the T superfamily, the major families among multidrug-resistant (MDR) Mycobacterium tuberculosis isolates from Senegal

To determine the molecular profile of the multidrug-resistant (MDR) strains of Mycobacterium tuberculosis isolated in Senegal. From 2011 to 2014, 43 MDR strains isolated at the National Reference Laboratory for Mycobacteria of the National Antituberculosis Program (NAP) were characterized by spoligotyping. Nine different spoligotypes were identified, three of which were unique, the other six forming clusters of two to nine isolates. The three principal families identified were the T superfamily (12/43, 27.90%), Beijing (9/43, 20.93%), and Latino-American-Mediterranean (LAM; 3/43, 6.97%). Twelve isolates could not be attributed to a particular lineage. The strains causing multidrug-resistant tuberculosis in Senegal belong to three main families: the T superfamily, Beijing, and LAM. Key words: Tuberculosis, spoligotypes, resistance, Senegal.
A Study on High Efficiency Video Coding Technique

HEVC, also known as H.265, stands for High Efficiency Video Coding which is a new video codec that will compress video files to half the size compared to the current encoding format, AVC/MPEG-4. That will be one-quarter the size of files compressed using the MPEG 2 codec that most cable-TV companies still employ. It can also obtain high video quality at the same bit rate using better data compression techniques. This technique will be very useful in mitigating increasing data sizes of next generation video qualities like 4k and 8k resolutions & increasing IP traffic over the internet. This paper analyses this technique, compares it to other existing encoding techniques and proposes a 3D extension to this technique.
Technology-Based Knowledge Systems

Knowledge is collected and organized into technology-based systems in various ways to support learning and performance. Four main types of systems are identified under the general term of knowledge systems : (1) expert or knowledge-based, (2) knowledge management, (3) knowledge communities, and (4) hybrid systems that combine elements of the other types. Expert systems are computer programs that use knowledge derived from human experts to provide guidance to novices. A number of these systems have been adapted to assist in learning. Expert systems use captured knowledge to help a computer program provide assistance to a user. In knowledge management systems, the knowledge is captured and organized for direct access by the user. The third type of system is aimed at facilitating direct human-to-human communication of knowledge and includes research that comes under the categories of communities of practice or knowledge communities. This area also includes informal knowledge sharing networks that emerge through such technologies as instant messaging. This chapter highlights common research issues that cut across the three approaches, including how knowledge is derived from human sources; how knowledge is encoded in a machine readable form; how collections of digital knowledge are organized using taxonomies, metadata, and ontology; and, finally, knowledge quality assurance.
Genome, transcriptome, and methylome in the conifer pathogen Heterobasidion parviporum

5/2018 Jonna Emilia Teikari Toxic and Bloom-forming Baltic Sea Cyanobacteria under Changing Environmental Conditions 6/2018 Juha Immanen Cytokinin Signaling in Hybrid Aspen Cambial Development and Growth 7/2018 Sanna Mäntynen Anaerobic Microbial Dechlorination of Polychlorinated Dibenzo-p-dioxins and Dibenzofurans in Contaminated Kymijoki River Sediments 8/2018 Johannes Cairns Low Antibiotic Concentrations and Resistance in Microbial Communities 9/2018 Samia Samad Regulation of Vegetative and Generative Reproduction in the Woodland Strawberry 10/2018 Silviya Korpilo An Integrative Perspective on Visitor Spatial Behaviour in Urban Green Spaces: Linking Movement, Motivations, Values and Biodiversity for Participatory Planning and Management 11/2018 Hui Zhang Responses of Arctic Permafrost Peatlands to Climate Changes over the Past Millennia 12/2018 Minna Santalahti Fungal Communities in Boreal Forest Soils: The Effect of Disturbances, Seasons and Soil Horizons 13/2018 Marika Tossavainen Microalgae – Platform for Conversion of Waste to High Value Products 14/2018 Outi-Maaria Sietiö The Role of Plant-Fungal Interaction for the Soil Organic Matter Degradation in Boreal Forest Ecosystem 15/2018 Nanbing Qin Effects of Dietary Management on the Energy Metabolism of Periparturient Dairy Cows: Regulation of Lipidome and Transcriptome 16/2018 Anu Humisto Antifungal and Antileukemic Compounds from Cyanobacteria: Bioactivity, Biosynthesis, and Mechanism of Action 17/2018 Vilma Sandström Telecouplings in a Globalizing World: Linking Food Consumption to Outsourced Resource Use and Displaced Environmental Impacts 1/2019 Yafei Zhao Evolution of Asteraceae Inflorescence Development and CYC/TB1-Like Gene Functions 2/2019 Swarnalok De Interactions of Potyviral Protein HCPro with Host Methionine Cycle Enzymes and Scaffolding Protein VARICOSE in Potato Virus A Infection 3/2019 Anirudra Parajuli The Effect of Living Environment and Environmental Exposure on the Composition of Microbial Community in Soil, on Human Skin and in the Gut 4/2019 Jaakko Leppänen Cladocera as Sentinels of Aquatic Mine Pollution 5/2019 Marjukka Lamminen Potential of Microalgae to Replace Conventional Protein Feeds for Sustainable Dairy Cow Nutrition 6/2019 Maisa Nevalainen Preparing for the Unprecedented – Moving Towards Quantitative Understanding of Oil Spill Impacts on Arctic Marine Biota Y E B
A Study of CT Versus MR Arthrography in Detection of Acetabular Cartilage Defects and Labral Tears

Background: the most important role of imaging in the preoperative period is to reveal labro-cartilaginous lesions in patients with chronic hip pain and suggested FAI. MRI particularly 3T MRI has a good ability to detect labral and chondral pathologies in FAI. Objective: to evaluate CT hip arthrography in the detection of acetabularlabral lesions and articular cartilage defects in comparison with MR arthrography in patients with chronic intractable hip pain. Patients and Methods: this is a cross sectional study in Cairo Scan Radiology center and Al-Azhar University hospital over 5 years period. The study included 61 patients who were referred for identification of source of chronic hip pain or assessing previous hip arthroscopic intervention. All cases were subjected to evaluation by both MDCT and MR arthrography. Confirmation of diagnosis was primarily based upon MR arthrography findings. Result: sixty-one patients were included in this study. Of them, 51 patients have been proved to have intra articular pathology; 31 males (61%) and 20 females (39%). Femoro-acetabular deformities were readily detectable via CT arthrography. Compared to MRA, CT arthrography had a sensitivity and specificity of 90.7% and 100% in detection of acetbularlabral lesions, 95% and 100% specificity in detection of femoral and acetabularchondral lesions, and 86% and 100% specificity in the detection of other intra articular pathologies, respectively. Conclusion: multidetector CT arthrography is an efficient alternative to MR arthrography in the evaluation of internal derangements of the hip.