Miracle-dz/UniFAR-FTUs huggingface dataset:
A Software Radio Development Platform PCP200, Partnering''C6x with Virtex FPGA

Software Radios have been widely studied as a solution to support multiple competing and incompatible air interface standards in future wireless communications. However, the current state of the art in general purpose digital signal processor (DSP) is inadequate to support this concept. In this paper, a Programmable Communications Processor platform (PCP2000), partnering Virtex Filed Programmable Gate Array (FPGA) with ‘C62x DSP Evm, is introduced to provide an ideal platform towards developing high complexity signal processing algorithms. As an example, the implementation of a dual-mode GSM/W-CDMA receiver based on software radio concepts is described.
A variational mode solver for optical waveguides based on quasi-analytical vectorial slab mode expansion

A flexible and efficient method for fully vectorial modal analysis of 3D dielectric optical waveguides with arbitrary 2D cross-sections is proposed. The technique is based on expansion of each modal component in some a priori defined functions defined on one coordinate axis times some unknown coefficient-functions, defined on the other axis. By applying a variational restriction procedure the unknown coefficient-functions are determined, resulting in an optimum approximation of the true vectorial mode profile. This technique can be related to both Effective Index and Mode Matching methods. A couple of examples illustrate the performance of the method.
Decision trees with minimal costs

We propose a simple, novel and yet effective method for building and testing decision trees that minimizes the sum of the misclassification and test costs. More specifically, we first put forward an original and simple splitting criterion for attribute selection in tree building. Our tree-building algorithm has many desirable properties for a cost-sensitive learning system that must account for both types of costs. Then, assuming that the test cases may have a large number of missing values, we design several intelligent test strategies that can suggest ways of obtaining the missing values at a cost in order to minimize the total cost. We experimentally compare these strategies and C4.5, and demonstrate that our new algorithms significantly outperform C4.5 and its variations. In addition, our algorithm's complexity is similar to that of C4.5, and is much lower than that of previous work. Our work is useful for many diagnostic tasks which must factor in the misclassification and test costs for obtaining missing information.
Stance Detection in Turkish Tweets

Stance detection is a classification problem in natural language processing where for a text and target pair, a class result from the set {Favor, Against, Neither} is expected. It is similar to the sentiment analysis problem but instead of the sentiment of the text author, the stance expressed for a particular target is investigated in stance detection. In this paper, we present a stance detection tweet data set for Turkish comprising stance annotations of these tweets for two popular sports clubs as targets. Additionally, we provide the evaluation results of SVM classifiers for each target on this data set, where the classifiers use unigram, bigram, and hashtag features. This study is significant as it presents one of the initial stance detection data sets proposed so far and the first one for Turkish language, to the best of our knowledge. The data set and the evaluation results of the corresponding SVM-based approaches will form plausible baselines for the comparison of future studies on stance detection.
Large-scale Nano-PLA Meshes with Efficient Logic Mapping . . — Architecture and Max-Clique Partitioning Algorithm

An area efficient architecture for organization of sublithographic PLAs(Programmable Logic Arrays) is proposed. Two-way maxclique clustering and partitioning algorithm is suggested for use on this architecture for efficient logic mapping. This algorithm bridges the barrier between the traditional schemes of Top-down partitioning and Bottomup clustering in VLSI design and gives a unified approach to the problem of logic mapping. The scheme is based on recent developments in heuristics for maximum clique search in an undirected graph using sequential coloring.
Is Tibet an Attractive Tourism Destination? A Comparative Study of People’s Organic Image in Mainland China and Hong Kong

This study seeks to explore the tourism destination image of Tibet, and further to compare the difference between the organic image of Mainland China and that of Hong Kong. The findings indicated that both group regarded “the natural and beautiful scenery” as the most important attractions of Tibet. The top three motivations of Mainland people were the mysteriousness, natural scenery, and novelty of Tibet”. Hong Kong tourists were most motivated by Tibet’s natural scenery mysteriousness, and culture. In terms of the concerns of traveling to Tibet, people in Mainland China cared most on health issue, while Hong Kong people concerned more on transportation. The findings of this study may provide useful guidance to marketing strategies and sustainable tourism development in Tibet.
Using Cloud Services to Develop Learning Scenarios from a Software Engineering Perspective

The term “Cloud Computing” does not primarily specify new types of core technologies but rather addresses features to do with integration, inter-operability and accessibility. Although not new, virtualization and automation are core features that characterize Cloud Computing. In this paper, we intend to explore the possibility of integrating cloud services with educational scenarios without re-defining neither the technology nor the usage scenarios from scratch. Our suggestion is based on certain solutions that have already been implemented and tested for specific cases.
Broadcast disks: data management for asymmetric communication environments

This paper proposes the use of repetitive broadcast as a way of augmenting the memory hierarchy of clients in an asymmetric communication environment. We describe a new technique called "Broadcast Disks" for structuring the broadcast in a way that provides improved performance for non-uniformly accessed data. The Broadcast Disk superimposes multiple disks spinning at different speeds on a single broadcast channel--in effect creating an arbitrarily fine-grained memory hierarchy. In addition to proposing and defining the mechanism, a main result of this work is that exploiting the potential of the broadcast structure requires a re-evaluation of basic cache management policies. We examine several "pure" cache management policies and develop and measure implementable approximations to these policies. These results and others are presented in a set of simulation studies that substantiates the basic idea and develops some of the intuitions required to design a particular broadcast program.
Metagenomic Evidence for H2 Oxidation and H2 Production by Serpentinite-Hosted Subsurface Microbial Communities

Ultramafic rocks in the Earth’s mantle represent a tremendous reservoir of carbon and reducing power. Upon tectonic uplift and exposure to fluid flow, serpentinization of these materials generates copious energy, sustains abiogenic synthesis of organic molecules, and releases hydrogen gas (H2). In order to assess the potential for microbial H2 utilization fueled by serpentinization, we conducted metagenomic surveys of a marine serpentinite-hosted hydrothermal chimney (at the Lost City hydrothermal field) and two continental serpentinite-hosted alkaline seeps (at the Tablelands Ophiolite, Newfoundland). Novel [NiFe]-hydrogenase sequences were identified at both the marine and continental sites, and in both cases, phylogenetic analyses indicated aerobic, potentially autotrophic Betaproteobacteria belonging to order Burkholderiales as the most likely H2-oxidizers. Both sites also yielded metagenomic evidence for microbial H2 production catalyzed by [FeFe]-hydrogenases in anaerobic Gram-positive bacteria belonging to order Clostridiales. In addition, we present metagenomic evidence at both sites for aerobic carbon monoxide utilization and anaerobic carbon fixation via the Wood–Ljungdahl pathway. In general, our results point to H2-oxidizing Betaproteobacteria thriving in shallow, oxic–anoxic transition zones and the anaerobic Clostridia thriving in anoxic, deep subsurface habitats. These data demonstrate the feasibility of metagenomic investigations into novel subsurface habitats via surface-exposed seeps and indicate the potential for H2-powered primary production in serpentinite-hosted subsurface habitats.
Near Minimax Optimal Players for the Finite-Time 3-Expert Prediction Problem

We study minimax strategies for the online prediction problem with expert advice. It has been conjectured that a simple adversary strategy, called COMB, is near optimal in this game for any number of experts. Our results and new insights make progress in this direction by showing that, up to a small additive term, COMB is minimax optimal in the finite-time three expert problem. In addition, we provide for this setting a new near minimax optimal COMB-based learner. Prior to this work, in this problem, learners obtaining the optimal multiplicative constant in their regret rate were known only when K = 2 or K → ∞. We characterize, when K = 3, the regret of the game scaling as √8/(9π)T ± log(T)2 which gives for the first time the optimal constant in the leading (√T) term of the regret.
QoS routing in wireless sensor networks—a survey

A wireless sensor network (WSN) is a one made up of small sensing devices equipped with processors, memory, and short-range wireless communication. Sensor nodes, are autonomous nodes, which include smart dust sensors, motes and so on. They co-operatively monitor physical or environmental conditions and send the sensed data to the sink node. They differ from traditional computer networks due to resource constraints, unbalanced mixture traffic, data redundancy, network dynamics, and energy balance. These kinds of networks support a wide range of applications that have strong requirements to reduce end-to-end delay and losses during data transmissions. When large numbers of sensors are deployed in a sensor field and are active in transmitting the data, there is a possibility of congestion. Congestion may occur due to buffer overflow, channel contention, packet collision, a high data rate, many to one nature, and so on. This leads to packet loss which causes a decrease in throughput and lifetime. Maximum throughput, energy efficiency and minimum error rate can be achieved by minimizing the congestion. A number of quality of service (QoS) techniques has been developed to improve the quality of the network. This article gives an overview of existing QoS techniques and a parametric comparison made with recent developments. This article mainly concentrates on network congestion in WSN environment.
Nonstructural Protein 1 of Influenza A Virus Interacts with Human Guanylate-Binding Protein 1 to Antagonize Antiviral Activity

Human guanylate-binding protein 1 (hGBP1) is an interferon-inducible protein involved in the host immune response against viral infection. In response to infection by influenza A virus (IAV), hGBP1 transcript and protein were significantly upregulated. Overexpression of hGBP1 inhibited IAV replication in a dose-dependent manner in vitro. The lysine residue at position 51 (K51) of hGBP1 was essential for inhibition of IAV replication. Mutation of K51 resulted in an hGBP1 that was unable to inhibit IAV replication. The viral nonstructural protein 1 (NS1) was found to interact directly with hGBP1. K51 of hGBP1 and a region between residues 123 and 144 in NS1 were demonstrated to be essential for the interaction between NS1 and hGBP1. Binding of NS1 to hGBP1 resulted in a significant reduction in both GTPase activity and the anti-IAV activity of hGBP1. These findings indicated that hGBP1 contributed to the host immune response against IAV replication and that hGBP1-mediated antiviral activity was antagonized by NS1 via binding to hGBP1.
Quadriceps strength predicts mortality in patients with moderate to severe chronic obstructive pulmonary disease

Background: Prognosis in chronic obstructive pulmonary disease (COPD) is poorly predicted by indices of air flow obstruction, because other factors that reflect the systemic nature of the disease also influence prognosis. Objective: To test the hypothesis that a reduction in quadriceps maximal voluntary contraction force (QMVC) is a useful predictor of mortality in patients with COPD. Methods: A mortality questionnaire was sent to the primary care physician of 184 patients with COPD who had undergone quadriceps strength measurement over the past 5 years. QMVC was expressed as a percentage of the patient’s body mass index. The end point measured was death or lung transplantation, and median (range) follow-up was 38 (1–54) months. Results: Data were obtained for 162 patients (108 men and 54 women) with a mean (SD) percentage of forced expiratory volume in 1 s (FEV1) predicted of 35.6 (16.2), giving a response rate of 88%. Transplant-free survival of the cohort was 93.5% at 1 year and 87.1% at 2 years. Cox regression models showed that the mortality risk increased with increasing age and with reducing QMVC. Only age (HR 1.72 (95% CI 1.14 to 2.6); p = 0.01) and QMVC (HR 0.91 (95% CI 0.83 to 0.99); p = 0.036) continued to be significant predictors of mortality when controlled for other variables in the multivariate analysis. Conclusion: QMVC is simple and provides more powerful prognostic information on COPD than that provided by age, body mass index and forced expiratory volume in 1 s.
Integrating safety analysis and requirements engineering

Some systems failures are due to defects in manufacturing and design, however that there are a significant number of system failures which result from errors, omissions and inconsistencies in the system requirements. We thus need methods to support a 'safe' requirements engineering process whose objectives are to specify system requirements such that system states which compromise safety are avoided and to include, along with the requirements, a justification or safety case which explains why the specified system is indeed safe. This paper describes the extension of a viewpoint-based requirements method to incorporate safety analysis.
Repetitive transcranial magnetic stimulation for Tourette syndrome

In a single-blinded, placebo-controlled, crossover repetitive transcranial magnetic stimulation (rTMS) trial, 16 patients with Gilles de la Tourette syndrome (GTS) received in random sequence 1 Hz motor, premotor, and sham rTMS, which each consisted of two 20-minute rTMS sessions applied on 2 consecutive days. In the 12 patients who completed the trial, there was no significant improvement of symptoms after any of the rTMS conditions as assessed with the Motor tic, Obsessions and compulsions, Vocal tic Evaluation Survey.
Interferon α Induces the Apoptosis of Cervical Cancer HeLa Cells by Activating both the Intrinsic Mitochondrial Pathway and Endoplasmic Reticulum Stress-Induced Pathway

The interferon α (IFN-α) has been often used as a sensitizing agent for the treatment of various malignancies such as hepatocellular carcinoma, malignant melanoma, and renal cell cancer by promoting the apoptosis of thesetumor cell types. However, the effect of IFN-α on cervical cancer remains unknown. In this study, HeLa cells were used as a testing model for the treatment of IFN-α on cervical cancer. The results indicate that IFN-α markedly inhibits the proliferation and induces the apoptosis of HeLa cells. The activation of caspase 3, the up-regulation of both Bim and cleaved poly (ADP-ribose) polymerase (PARP) 1, the down-regulation of Bcl-xL, as well as the release of cytochrome c from mitochondria were significantly induced upon IFN-α treatment, indicating that the intrinsic apoptotic pathway could be activated by IFN-α treatment. In addition, caspase 4—which is involved in the endoplasmic reticulum (ER) stress-induced apoptosis—was activated in response to IFN-α treatment. Knocking down caspase 4 by small interfering RNA (siRNA) markedly reduced the IFN-α-mediated cell apoptosis. However, no significant changes in the expressions of caspases 8 and 10 were observed upon IFN-α treatment, indicating that the apoptosis caused by IFN-α might be independent of the extrinsic apoptotic pathway. These findings suggest that IFN-α may possess anti-cervical cancer capacity by activating cell apoptosis via the intrinsic mitochondrial pathway and caspase-4-related ER stress-induced pathway.
Exploring the Ideological Nature of Journalists' Social Networks on Twitter and Associations with News Story Content

The present work proposes the use of social media as a tool for better understanding the relationship between a journalists' social network and the content they produce. Specifically, we ask: what is the relationship between the ideological leaning of a journalist's social network on Twitter and the news content he or she produces? Using a novel dataset linking over 500,000 news articles produced by 1,000 journalists at 25 different news outlets, we show a modest correlation between the ideologies of who a journalist follows on Twitter and the content he or she produces. This research can provide the basis for greater self-reflection among media members about how they source their stories and how their own practice may be colored by their online networks. For researchers, the findings furnish a novel and important step in better understanding the construction of media stories and the mechanics of how ideology can play a role in shaping public information.
Interaction Analysis for Supporting Students' Self-Regulation during Blog-based CSCL Activities

Self-regulated learning is an important means of supporting students’ self-awareness and self-regulation level so as to enhance their motivation and engagement. Interaction Analysis (IA) contributes to this end, and its use in studying learning dynamics involved in asynchronous Computer-Supported Collaborative Learning (CSCL) activities has rightfully increased in recent years. This paper presents a case study regarding the impact IA graphs have on students’ self-regulation, during a blog-based learning activity. More specifically, 52 secondary education students – a control group (25 students without IA toolkit support) and an experimental group (27 students with IA toolkit support) – used a blog, as a communication and information management medium for creating Scratch games. The statistical analysis of their responses to the Self-Regulation Questionnaire, before and after the activity, indicates that IA graphs facilitated their self-regulation capacity. The results support the initial hypothesis, namely that IA constitutes an important module for self-regulation in CSCL settings, enhancing the collaborative learning activity
Vapor Phase Hydrogen Peroxide Imaging Using Photofragmentation Laser-Induced Fluorescence

Imaging of vapor-phase H<inf>2</inf>O<inf>2</inf> concentrations is performed using photofragmentation LIF. An Nd:YAG-laser is used for photolysis and a dye laser for LIF on OH generated in the photolysis process. Detection limit is ∼30 ppm.
Spinal en Plaque Meningiomas: A Contemporary Experience

OBJECTIVE:Spinal en plaque meningiomas are rare and challenging lesions because of their tendency to induce spinal arachnoiditis. The surgical treatment of this type of meningioma is more complex than that of classic meningioma. METHODS:We report seven cases of spinal en plaque meningiomas and review all the cases reported in the literature accessible to us by a MEDLINE search. RESULTS:All patients underwent microsurgery. Complete tumor removal was achieved in three patients. Subtotal removal was performed in four patients. A permanent neurological worsening was observed in one patient. CONCLUSION:Spinal meningiomas en plaque bear a prognosis poorer than that of classic meningiomas with regard to the possibility of a definitive surgical cure because recurrence or postoperative arachnoiditis occurs frequently. Total surgical removal should be attempted only when a clear plane of cleavage between tumor and arachnoid exists.
The Hepatitis B Virus Core Promoter Is Strongly Activated by the Liver Nuclear Receptor Fetoprotein Transcription Factor or by Ectopically Expressed Steroidogenic Factor 1

ABSTRACT Orphan nuclear receptor fetoprotein transcription factor (FTF) was previously identified as a specific regulator of the α1-fetoprotein gene during early liver development and in response to hormonal signals (L. Galarneau, J.-F. Paré, D. Allard, D. Hamel, L. Lévesque, J. D. Tugwood, S. Green, and L. Bélanger, Mol. Cell. Biol. 16:3853–3865, 1996). Here we report a functional analysis of FTF interactions with the hepatitis B virus (HBV) nucleocapsid promoter. DNA-protein-binding assays show that the HBV core promoter contains two high-affinity FTF-binding sites and a third, lower-affinity site shared with other receptors. Transfections in HepG2, Hep3B, and PLC/PRF/5 hepatoma cells using chloramphenicol acetyltransferase reporter genes with the nucleocapsid promoter linked or not linked to enhancer I indicate that FTF is a potent activator of the HBV core promoter, more efficient than HNF4α, HNF3α, HNF3β, or C/EBPα. Steroidogenic factor 1, a close FTF homolog which binds to the same DNA motif and is expressed ectopically in HepG2 cells, seems to be an even stronger inducer than FTF. Point mutations of the FTF-binding sites indicate direct FTF activatory effects on the core promoter and the use of both high-affinity sites for productive interaction between the core promoter and enhancer I. Coexpression assays further indicate that FTF and HNF4α are the most efficient partners for coactivation of the pregenomic core promoter, which may largely account for the hepatic tropism and the early amplification of HBV infection. Carboxy terminus-truncated FTF behaves as a dominant negative mutant to compete all three FTF sites and strongly deactivate core promoter interactions with enhancer I; this suggests possible new ways to interfere with HBV infection.
Relaxation Methods for Minimum Cost Ordinary and Generalized Network Flow Problems

We propose a new class of algorithms for linear cost network flow problems with and without gains. These algorithms are based on iterative improvement of a dual cost and operate in a manner that is reminiscent of coordinate ascent and Gauss-Seidel relaxation methods. We compare our coded implementations of these methods with mature state-of-the-art primal simplex and primal-dual codes, and find them to be several times faster on standard benchmark problems, and faster by an order of magnitude on large, randomly generated problems. Our experiments indicate that the speedup factor increases with problem dimension.