Miracle-dz/UniFAR-FTUs huggingface dataset:
Adaptive Transmit Antenna Selection and Power Allocation Scheme for Turbo-Blast System with Imperfect Channel State Information

In this paper, a new technique that combines adaptive transmit antenna selection, transmit power allocation and iterative detection is introduced for the modifled Turbo-BLAST system. At the transmitter, in order to minimize the BER performance of the overall system, an adaptive transmit antenna selection scheme is proposed to select the appropriate antenna subset for the actual transmission, and the proper power is allocated for the selected antennas subject to the total transmit power constraint. At the receiver the modifled MMSE detector taking the imperfect CSI into account is used to remove the co-antenna interference. Finally the turbo principle is employed for iterative detection to further lower the BER results. Simulation results show that the introduced adaptive transmit antenna selection and power allocation algorithm can signiflcantly improve the BER performance, and the iterative detection technique can further enhance the performance.
The Demand for Alcohol, Tobacco and Marijuana: International Evidence

Introduction Food, soft-drinks, tobacco, alcohol and marijuana consumption: an overview Tobacco consumption Alcohol consumption Marijuana consumption A differential approach to demand analysis Parameterization, estimation and testing hypotheses Demand for food, tobacco, alcohol and soft drinks Demand for beer, wine and spirits The economics of marijuana consumption Alcohol misuse and control policies Tobacco control policies Consumption patterns of five consumer goods A summary Bibliography Index.
Design and Development of a Core Grid Ontology ?

In this paper, we introduce a core Grid ontology that defines fundamental Grid domain concepts, vocabularies and relationships. This ontology is based on a general model of Grid infrastructures, and described in Web Ontology Language OWL. Such an ontology can play an important role in building Grid-related Knowledge base and in supporting the realization of the Semantic Grid.
A Novel Weighted Cooperative Routing Algorithm Based on Distributed Relay Selection

Typically wireless multi-hop ad hoc and sensor networks utilize protocols that relay packets hop-by-hop along a path connecting source node to sink node. The emerging cooperative routing (CR) methodology, however, can obtain distinct performance gain by selecting extra relay to forward data. This study presents a novel distributed weighted cooperative routing algorithm (DWCRA) which selects the "best" relay with the optimal weighted metric for cooperative transmission in a distributed manner. The weighted metric of relay selection strategy comprises of remaining energy of relays and channel state information (CSI) of each source-relay-sink pair. The simulation is implemented on NS-2 platform and results show that, compared to non-cooperative DSDV routing protocol, DWRCA achieves a delivery-lifetime tradeoff between maximal remaining energy algorithm (MREA) and optimal channel state algorithm (OCSA). In addition, different performance demand can be met by dynamic coordination of the weighted factors
Investigation of parasitic and viral pathogens in mussels (Mytilus galloprovincialis) in the Gulf of Izmir, Turkey

Objectives: To investigate Microsporidia spp. parasite, hepatitis A virus (HAV), and norovirus (NoV) contamination in mussels collected from 8 stations in the inner, middle, and outer regions of the Gulf of Izmir. Methods: In this cross-sectional study carried out between August 2009 and September 2010 in the Gulf of Izmir, Turkey, 15 mussels collected from each of the stations each season were pooled and homogenized to create a single representative sample. Thirty representative samples were available for analysis. Direct polymerase chain reaction (PCR), RT-nested PCR, and RT-booster PCR were used to investigate the pathogens. Results: The mussels were negative for Microsporidia spp. , but 8 (26.7%) samples analyzed were positive for HAV and 9 (30%) were positive for NoV. Excluding Foca and Gediz, viral contamination was detected in all of the stations sampled. Conclusion: Our results suggest that viral contamination is present in mussels in the Gulf of Izmir and may pose a potential threat to human health in the region. Necessary measures should be taken to prevent future illness due to these pathogens.
Signal Separation using Non-negative Matrix Factorization Based on R1-norm

Nonnegative Matrix Factorization (NMF) based methods have found use in the context of blind source separation, semi-supervised, and unsupervised learning. These techniques require the use of a suitable cost function to determine the optimal factorization, and most work has focused on the use of least square formulation which is prone to large noise and outliers. In this paper we developed robust NMF algorithm using 1 R -norm which exhibit stability and robustness w.r. t. large noises. This algorithm is as efficient as the algorithms for least square formulations, avoiding the significant computational complexities routinely associated with 1 R -norm formulations. The experimental show that 1 R -NMF can effectively separate the observed that contain outliers better than standard NMF. [ W. kider and M. E. Abd El Aziz. Signal Separation using Non-negative Matrix Factorization Based on R1norm. Life Sci J 2012;9(4):703-707] (ISSN:1097-8135). http://www.lifesciencesite. com. 110
Principles and Model for Web Dataspace

Web information integrated management system requires a powerful and versatile data model that is able to represent a highly heterogeneous mix of data such as web pages, XML, deep web, files, etc. It requires access to both structured and unstructured data. Such collections of data have been referred to as dataspace. In order to build a web dataspace support platform, we described some principles. According to these principles, we design architecture for the web dataspace support platform. Based on the RDF model, we present a web dataspace Data Model. This model is able to represent all of the above data in a single, powerful yet simple data model. It can represent unstructured, semi-structured and structured data inside a single model.
Oxaliplatin-induced Pulmonary Fibrosis: Two Case Reports

Oxaliplatin with infusional 5-fluorouracil plus leucovorin (FOLFOX regimen) is the one of the standard chemotherapy regimens for treating a colorectal carcinoma. The most common side effects include neutropenia, diarrhea, vomiting and peripheral neuropathy, and these are moderate and manageable. However, pulmonary toxicity is rarely reported to be associated with the FOLFOX regimen. Moreover, there is no established guideline for the management of this side effect. Here, along with a literature review, we report two cases of rapidly developing pulmonary fibrosis related to the use of the FOLFOX regimen in patients with colorectal carcinomas.
Evaluation of Probabilistic Occupancy Map for Player Tracking in Team Sports

In this paper we focus on tracking of players in team sports with multiple cameras. We evaluate a state of the art multi-camera multi-target tracking algorithm on a novel floorball dataset. We chose recent Probabilistic Occupancy Map and K-Shortest Path algorithms with a publicly available implementation that enables easy deployment. Both algorithms are mathematically well funded and capable of near real-time performance. We show quantitative evaluation of the algorithms on a real-world problem, and demonstrate influence of different background subtraction methods that are a necessary preprocessing step.
Study on maturity level transition mechanism of knowledge management

The maturity levels and key process areas are the important parts of enterprise knowledge management maturity model. The implementation of key processes areas by groups is the basis to achieve maturity level transitions; it can promote enterprise knowledge management to evolve from the ad-hoc, chaotic stage to mature, disciplined stages. This paper firstly analyzed the characteristics and thoughts of maturity models, then comprehensively compared the key process areas of many KMMM, established the transition benchmark of knowledge management maturity level, and discussed in depth the transition mechanism of maturity level in order to help effectively implementing knowledge management projects.
The Burrows-Wheeler compression algorithm is even better than what you have thought

The best compression algorithm today for English text is based on the Burrows-Wheeler transform. This algorithm (whose common implementation is bzip2) consists of the following three essential steps: 1) Obtain the Burrows-Wheeler transform of the text, 2) Convert the transform into a sequence of integers using the move-to-front algorithm, 3) Encode the integers using arithmetic code or any order-0 encoding (possibly with run length encoding). In this paper we achieve a strong bound on the worst-case compression ratio of this algorithm, that is signiflcantly better than bounds known to date and is obtained via simple analytical techniques. Speciflcally, for any input string s, and „ > 1, the length of the compressed string is bounded by „¢jsjHk(s) + log(‡(„))¢jsj + gk where Hk is the k-th order empirical entropy, gk is a constant depending only on k and on the size of the alphabet, and ‡(„) = 1 1„ + 1 2„ + : : : is the standard zeta function. In fact we prove a stronger result: That this bound without the additive term gk holds when we replace Hk(s) by the sum of the logarithms of the integers obtain by the move-to-front encoding of the transform. This reflned bound is tight and close to the actual compression achieved in practice. To obtain this result we prove a tight result on the compressibility of integer sequences, which is of independent interest.
Morphological Filtering and Hierarchical Deformation for Partially Overlapping Cell Segmentation

Accurate cell segmentation is an important and long-standing challenge in biomedical image analysis due to large variations in shape and boundary ambiguity. In this paper, we present a segmentation framework for partially overlapping cervical cells. The proposed method starts by cellular clump estimation with morphological reconstruction. Subsequently, the nuclei inside the cellular clumps are located by H-maxima transformation and thresholding. The cytoplasm of each detected nucleus is finally delineated with hierarchical deformation based on landmarks and shape dictionaries. The proposed approach is tested on a cervical smear image dataset containing single and partially overlapping cells. The results demonstrate that our approach can achieve more accurate and stable cytoplasmic segmentation, better nuclear segmentation, and lower time complexity, compared to a state-of-the-art approach.
Writer identification from handwriting text lines

In this paper, new techniques have been introduced for revealing the individual features of a person's handwriting pattern to facilitate text-independent off-line writer identification. These techniques are aimed at designing a dynamic model which can be formalized according to any handwritten text line. Various combinations of the extracted features are applied to three well known classifiers for evaluating the contribution of features to the correct identification rate. The K-NN, GMM, and Normal Density Discriminant Function (NDDF) Bayes classifiers are used in the present identification model. The experimental studies are conducted on the IAM database containing 650 writers. The performance of the extracted features is also analyzed with respect to number of writers in the query. The remarkable identification rates obtained from the three classifiers clearly indicate that the proposed feature extraction techniques can be effectively used in writer identification systems.
Dynamic Style Analysis and Applications

We analyze the shortcomings of existing multi-factor models based on portfolio performance data in detecting investment portfolio dynamics such as gradual style drift or rapid changes in strategy. We then lay the groundwork for a new approach, which we call Dynamic Style Analysis (DSA), representing a time-series multi-factor portfolio analysis model. The major concepts of the new methodology are gradually introduced and applied to analyses of both model portfolios and well-known US equity mutual funds. By comparing publicly available holdings data with results obtained with DSA, we demonstrate both the superiority of the new model and its remarkable accuracy in detecting portfolio dynamics. We also address issues such as the computational complexity of DSA and its practical applications in the areas of risk management, performance measurement and investment research. One of the major applications of the new methodology lies in hedge fund due diligence and risk monitoring, where the importance of uncovering and controlling hidden factor dynamics is especially valuable given the limited transparency of hedge funds.
BootOX: Bootstrapping OWL 2 Ontologies and R2RML Mappings from Relational Databases

In this demo paper we present BOOTOX, a system facilitating ontology and mapping development by their automatic extraction (i.e., bootstrapping) from relational databases. BOOTOX has a number of advantages: it allows to control the OWL 2 profile of the output ontologies, and to bootstrap complex and provenance mappings, which are beyond the W3C direct mapping specification. Moreover, BOOTOX allows to import pre-existing ontologies.
On the matching conditions for the collapsing cylinder

We review the matching conditions for a collapsing anisotropic cylindrical perfect fluid, recently discussed in the literature (2005 {\it Class. Quantum Grav.} {\bf 22} 2407). It is shown that radial pressure vanishes on the surface of the cylinder, contrary to what is asserted in that reference. The origin of this discrepancy is to be found in a mistake made in one step of the calculations. Some comments about the relevance of this result in relation to the momentum of Einstein--Rosen waves are presented.
Personality in Sanctuary-Housed Chimpanzees: A Comparative Approach of Psychobiological and Penta-Factorial Human Models

We evaluate a sanctuary chimpanzee sample (N = 11) using two adapted human assessment instruments: the Five-Factor Model (FFM) and Eysenck's Psychoticism-Extraversion-Neuroticism (PEN) model. The former has been widely used in studies of animal personality, whereas the latter has never been used to assess chimpanzees. We asked familiar keepers and scientists (N = 28) to rate 38 (FFM) and 12 (PEN) personality items. The personality surveys showed reliability in all of the items for both instruments. These were then analyzed in a principal component analysis and a regularized exploratory factor analysis, which revealed four and three components, respectively. The results indicate that both questionnaires show a clear factor structure, with characteristic factors not just for the species, but also for the sample type. However, due to its brevity, the PEN may be more suitable for assessing personality in a sanctuary, where employees do not have much time to devote to the evaluation process. In summary, both models are sensitive enough to evaluate the personality of a group of chimpanzees housed in a sanctuary.
The Turn-of-the-Month-Effect: Evidence from Periodic Generalized Autoregressive Conditional Heteroskedasticity (PGARCH) Model

The current study examines the turn of the month effect on stock returns in 20 countries. This will allow us to explore whether the seasonal patterns usually found in global data; America, Australia, Europe and Asia. Ordinary Least Squares (OLS) is problematic as it leads to unreliable estimations; because of the autocorrelation and Autoregressive Conditional Heteroskedasticity (ARCH) effects existence. For this reason Generalized GARCH models are estimated. Two approaches are followed. The first is the symmetric Generalized ARCH (1,1) model. However, previous studies found that volatility tends to increase more when the stock market index decreases than when the stock market index increases by the same amount. In addition there is higher seasonality in volatility rather on average returns. For this reason the Periodic-GARCH (1,1) is estimated. The findings support the persistence of the specific calendar effect in 19 out of 20 countries examined.
Improvements and Future Challenges for the Research Infrastructure: Firm Level Data

This article discusses the use of enterprise- and establishment-level data from official statistics to document stylized facts, to motivate assumptions used in formal theoretical models, to test hypotheses derived from theoretical models, and to evaluate policy measures. It shows how these data can be accessed by researchers in Germany today and reports on recent developments that will offer new and improved datasets that combine data collected in separate surveys and by different agencies. The paper makes three recommendations for future developments in this area: (1) change the law to make the combination of data collected by different producers easier, (2) combine firm-level data across national borders and make these data available for researchers, and (3) find ways to enable researchers in Germany to work with confidential firm-level data via remote access 24 hours a day and 365 days per year.
Voltage driven electrowetting based microfluidic operations for efficient droplet routing in digital microfluidic biochips

Electrowetting based operation can be effectively used to enhance the performance throughput of the programmable lab-on-chips (LOCs). These chips are also known as digital microfluidic biochips (DMFBs). In this work, initially we have presented a study on the effect of external actuation voltage in various parameters like transport velocity and contact angles during droplet movement on DMFB, in the realm of surface hysteresis. Next, a greedy heuristic method is adopted in conjunction with droplet velocity lookup under varying range of voltage actuation to perform improved droplet routing on digital microfluidic biochips. Here a specified routing time, termed as latest arrival time (LAT) is calculated in an ideal case, without considering practical electrowetting effects. Then a stepwise voltage increment is performed through the droplet routing paths to reach the specified target location in time. Goal of the proposed method is to achieve a specified routing time for all the droplets towards their destinations. Experimental analysis ascertains the suitability of this technique in enhancing the throughput of an LOC in terms of transport time reduction, and elimination of any failed net during routing.
Towards a decentralized overlay for real-time live streaming: CHARMS meets the web

In recent years, the fifth revision of the HyperText Markup Language standard (HTML5) has promoted the porting of traditional desktop applications to the Web, thus allowing the rise of Rich Internet Applications (RIAs). Additionally, the progressive support to Web Real-Time Communication (WebRTC) standard in modern browsers for real-time communications is accelerating this process, enabling the migration of a number of complex network applications and services to Web, including peer-to-peer (P2P) overlays. At the same time, the increase of bandwidth in access networks enables end-users to become content producers too. Taking into consideration the aforementioned factors, this paper introduces a preliminary proposal of metrics and technologies to move towards a decentralized cooperative architecture for large scale, real-time live stream content delivery based on WebRTC, with no need of a Content Delivery Network (CDN) infrastructure. Such metrics and technologies are introduced to smooth the way for a transition in such direction of the already described and implemented CHARMS (Cooperative Hybrid Architecture for Relaying Multimedia Streams) architecture.
Tolerance to drought and salt stress in plants: Unraveling the signaling networks

Tolerance of plants to abiotic stressors such as drought and salinity is triggered by complex multicomponent signaling pathways to restore cellular homeostasis and promote survival. Major plant transcription factor families such as bZIP, NAC, AP2/ERF, and MYB orchestrate regulatory networks underlying abiotic stress tolerance. Sucrose non-fermenting 1-related protein kinase 2 and mitogen-activated protein kinase pathways contribute to initiation of stress adaptive downstream responses and promote plant growth and development. As a convergent point of multiple abiotic cues, cellular effects of environmental stresses are not only imbalances of ionic and osmotic homeostasis but also impaired photosynthesis, cellular energy depletion, and redox imbalances. Recent evidence of regulatory systems that link sensing and signaling of environmental conditions and the intracellular redox status have shed light on interfaces of stress and energy signaling. ROS (reactive oxygen species) cause severe cellular damage by peroxidation and de-esterification of membrane-lipids, however, current models also define a pivotal signaling function of ROS in triggering tolerance against stress. Recent research advances suggest and support a regulatory role of ROS in the cross talks of stress triggered hormonal signaling such as the abscisic acid pathway and endogenously induced redox and metabolite signals. Here, we discuss and review the versatile molecular convergence in the abiotic stress responsive signaling networks in the context of ROS and lipid-derived signals and the specific role of stomatal signaling.
A Critical View on Internet Voting Technology

We present a set of requirements for Internet voting protocols. We also present a short overview of the most prominent Internet voting protocols published so far, and we provide a comparative evaluation of those protocols, using the set of requirements we have developed. We proceed with discussing our thoughts regarding possible improvements in e-voting protocols. Internet is an application with a vision to the future. Nevertheless, a lot of work needs to be done before it can be accepted for large-scale elections.
Discovering Popular Point of Interests for Tourism with Appropriate Names from Social Data Analysis

This paper proposes a method for determining an appropriate names of popular POIs (Point of Interests) obtained in a clustering-based social spatial data analysis. The proposed method utilizes several reverse geocoding APIs, such as Foursquare and Google, and selects the most probable name for each cluster. In addition, the author tries to figure out the adequate dataset size when the proposed name assign method is used. Because the proposed name assign method is not affected by the size of dataset. By using the collected data, more than 4 million geo-tagged photos of 5 cities from Flickr, the author confirmed that the proposed method can assign more proper name for the clustering results compared with a conventional tag-based name assign method, even if the size of dataset is small.