Miracle-dz/UniFAR-FTUs huggingface dataset:
Salmonella Typhi Bactericidal Antibodies Reduce Disease Severity but Do Not Protect against Typhoid Fever in a Controlled Human Infection Model

Effective vaccines against Salmonella Typhi, a major cause of febrile illness in tropical regions, can have a significant effect as a disease control measure. Earlier work has shown that immunization with either of two Salmonella Typhi vaccines, licensed Ty21a or candidate M01ZH09, did not provide full immunity in a controlled human infection model. Here, we describe the human humoral immune responses to these oral vaccines and their functional role in protection after challenge with S. Typhi. Serum, obtained from healthy volunteers before and after vaccination with Ty21a or M01ZH09 or placebo and before and after oral challenge with wild-type S. Typhi, was assessed for bactericidal activity. Single-dose vaccination with M01ZH09 induced an increase in serum bactericidal antibodies (p = 0.001) while three doses of Ty21a did not. No association between bactericidal activity and protection against typhoid after challenge was seen in either vaccine arm. Bactericidal activity after vaccination correlated significantly with delayed disease onset (p = 0.013), lower bacterial burden (p = 0.006), and decreased disease severity scores (p = 0.021). Depletion of antibodies directed against lipopolysaccharide significantly reduced bactericidal activity (p = 0.009). We conclude that antibodies induced after ingestion of oral live-attenuated typhoid vaccines or after challenge with wild-type S. Typhi exhibit bactericidal activity. This bactericidal activity is mediated by anti-O:LPS antibodies and significantly reduces clinical symptoms but does not provide sterile immunity. This directs future vaccine studies toward other antigens or mechanisms of protection against typhoid.
Power saving techniques in mbms multicast mode

Multimedia Broadcast Multicast Services (MBMS) was introduced in Third Generation Partnership Project (3GPP) Release 6 in order to more efficiently use network and radio resources for the transmission of multimedia services both in the core network and, most importantly, in the air interface of UTRAN (UMTS Terrestrial Radio Access Network). From the radio perspective, MBMS includes point-to-point (PtP) and point-to-multipoint (PtM) modes. The latter aims to overcome network congestion when a large number of users request the same content. One of the most important aspects in MBMS is power control. The fact that Node B's transmission power is a limited resource and must be shared among all MBMS users in a cell indicates the need for power control during an MBMS service. Techniques, such us rate splitting and mixed usage of transport channels can be used to reduce the power requirement of delivering multicast traffic for MBMS users. To this direction, this paper presents simulation results that will reinforce the need for the usage of such techniques and will reveal the amount of power that is saved.
Collective Tweet Wikification based on Semi-supervised Graph Regularization

Wikification for tweets aims to automatically identify each concept mention in a tweet and link it to a concept referent in a knowledge base (e.g., Wikipedia). Due to the shortness of a tweet, a collective inference model incorporating global evidence from multiple mentions and concepts is more appropriate than a noncollecitve approach which links each mention at a time. In addition, it is challenging to generate sufficient high quality labeled data for supervised models with low cost. To tackle these challenges, we propose a novel semi-supervised graph regularization model to incorporate both local and global evidence from multiple tweets through three fine-grained relations. In order to identify semanticallyrelated mentions for collective inference, we detect meta path-based semantic relations through social networks. Compared to the state-of-the-art supervised model trained from 100% labeled data, our proposed approach achieves comparable performance with 31% labeled data and obtains 5% absolute F1 gain with 50% labeled data.
Big Data: Understanding Big Data

Steve Jobs, one of the greatest visionaries of our time was quoted in 1996 saying "a lot of times, people do not know what they want until you show it to them" [38] indicating he advocated products to be developed based on human intuition rather than research. With the advancements of mobile devices, social networks and the Internet of Things, enormous amounts of complex data, both structured and unstructured are being captured in hope to allow organizations to make better business decisions as data is now vital for an organizations success. These enormous amounts of data are referred to as Big Data, which enables a competitive advantage over rivals when processed and analyzed appropriately. However Big Data Analytics has a few concerns including Management of Data-lifecycle, Privacy & Security, and Data Representation. This paper reviews the fundamental concept of Big Data, the Data Storage domain, the MapReduce programming paradigm used in processing these large datasets, and focuses on two case studies showing the effectiveness of Big Data Analytics and presents how it could be of greater good in the future if handled appropriately.
Predicative Adjectives: An Unsupervised Criterion to Extract Subjective Adjectives

We examine predicative adjectives as an unsupervised criterion to extract subjective adjectives. We do not only compare this criterion with a weakly supervised extraction method but also with gradable adjectives, i.e. another highly subjective subset of adjectives that can be extracted in an unsupervised fashion. In order to prove the robustness of this extraction method, we will evaluate the extraction with the help of two different state-of-the-art sentiment lexicons (as a gold standard).
Preparation, characterization and antibacterial properties against E. coli K88 of chitosan nanoparticle loaded copper ions

The present study was conducted to prepare and characterize chitosan nanoparticle loaded copper ions, and evaluate their antibacterial activity. Chitosan nanoparticles were prepared based on ionotropic gelation, and then the copper ions were loaded. The particle size, zeta potential and morphology were determined. Antibacterial activity was evaluated against E. coli K88 by determination of the minimum inhibitory concentration (MIC) and minimum bactericidal concentration (MBC) in vitro. Results showed that the antibacterial activity was significantly enhanced by the loading of copper ions compared to those of chitosan nanoparticles and copper ions. The MIC and MBC of chitosan nanoparticle loaded copper ions were 21 times and 42 times lower than those of copper ions, respectively. To confirm the antibacterial mechanism, morphological changes of E. coli K88 treated by chitosan nanoparticle loaded copper ions were dynamically observed with an atomic force microscope (AFM). It was found that chitosan nanoparticle loaded copper ions killed E. coli K88 through damage to the cell membrane.
In Silico Fragment Screening by Replica Generation (FSRG) Method for Fragment-Based Drug Design

We developed a new in silico screening method, which is a structure-based virtual fragment screening with protein-compound docking. The structure-based in silico screening of small fragments is known to be difficult due to poor surface complementarity between protein surfaces and small compound (fragment) surfaces. In our method, several side chains were attached to the fragment in question to generate a set of replica molecules of different sizes. This chemical modification enabled us to select potentially active fragments more easily than basing the selection on the original form of the fragment. In addition, the Coulombic and hydrogen bonding interactions were ignored in the docking simulation to reduce the variety of chemical modifications. Namely, we focused on the sizes and the shapes of the side chains and could ignore the atomic charges and types of elements. This procedure was validated in the screenings of inhibitors of six target proteins using known active compounds, and the results revealed that our procedure was effective.
Fast Particle Loss-Cone Measurements by Angular Resolved Multi-Sightline Neutral Particle Analyzer (ARMS-NPA) in Large Helical Device (LHD)

The possibility of the fast particles loss-cone regions on the helical devices has been predicted theoretically. However the loss-cone region could not be measured so far by existing diagnostics. In order to check it experimentally the novel 20-sightline ARMS-NPA has been created on LHD. Two LHD ports were reserved to make a scan of plasma in horizontal plane. One port is for scanning of mostly tangentially emitted plasma and another one is for precise scan of perpendicular region in horizontal plane. In order to observe as wider as possible range of pitch angles, first multi-sightline measurements were made at the tangential port. Obtained data demonstrated the systematic decrease of fast particle population in the sightlines near perpendicular direction (from 95 to 100 degrees pitch-angle range) which can not be explained by the influence of the geometrical factor. The assumption of the loss-cone presence in the perpendicular region of LHD plasma was made. However tangential port appeared to be not sufficient for scanning of perpendicular region and only the edge part of possible loss-cone region could be observed. Same time it was complained that observed effect was not due to the loss-cone but due to the edge effect of diagnostic. To clarify the situation with possible loss-cone region the additional chamber of NPA was installed at perpendicular port. In this paper the experimental results obtained by horizontal scan of plasma column in perpendicular region are presented. Precise fast particle angular distribution in horizontal region and loss-cone region are shown evidently for the first time. Experimental data are compared with theoretical estimations.
The Advanced Computing Systems Association Improving Application Performance through Swap Compression Improving Application Performance through Swap Compression

The performance of large applications tends to be poor due to the high overhead added by the swapping mechanism. The same problem may be found in highly-loaded multi-programmed systems where many of the running applications have to use the swap space in order to be able to execute at the same time. Furthermore, those large applications might not be able to run on laptop or home computers as their resources are usually smaller than the ones found in an office system. In this paper, we present a solution to both problems that we have implemented in the Linux kernel. The idea consists of compressing the swapped pages and keeping them in a swap cache whenever possible. We have tested this new mechanism with a set of real applications obtaining a significant performance improvement.
Social Justice Leadership in Action: The Case of Tony Stewart*

Reflecting on the 140th anniversary of the Fourteenth Amendment (ratified July, 1868), this qualitative case study described a response by educator-activist Tony Stewart to the Aryan Nations, a neo-Nazi hate group that attempted to intimidate Stewart’s community, Coeur d’ Alene, Idaho, between 1972-2000. Stewart galvanized community response using a social justice agenda. We interviewed Stewart and essential community members, and examined legal documents, articles, and documentaries. Findings indicated Stewart’s leadership of public education and response via an anti-racism task force reduced and then defeated the group’s viability. Educational practices included strategic planning and community outreach. The study revealed a social justice response to hate groups that educators and community leaders potentially can replicate in similar situations.
Segment-based Fine-grained Emotion Detection for Chinese Text

Emotion detection has been extensively studied in recent years. Current baseline methods often use token-based features which cannot properly capture more complex linguistic phenomena and emotional composition in fine grained emotion detection. A novel supervised learning approach―segment-based fine-grained emotion detection model for Chinese text has been proposed in this paper. Different from most existing methods, the proposed model applies the hierarchical structure of sentence (e.g., dependency relationship) and exploits segment-based features. Furthermore, the emotional composition in short text is addressed by using the log linear model. We perform emotion detection on our dataset: news contents, fairly tales, and blog dataset, and compare our proposed method to representative existing approaches. The experimental results demonstrate the effectiveness of the proposed segment-based model.
Glass-forming property of hydroxyectoine is the cause of its superior function as a desiccation protectant

We were able to demonstrate that hydroxyectoine, in contrast to ectoine, is a good glass-forming compound. Fourier transform infrared and spin label electron spin resonance studies of dry ectoine and hydroxyectoine have shown that the superior glass-forming properties of hydroxyectoine result from stronger intermolecular H-bonds with the OH group of hydroxyectoine. Spin probe experiments have also shown that better molecular immobilization in dry hydroxyectoine provides better redox stability of the molecules embedded in this dry matrix. With a glass transition temperature of 87°C (vs. 47°C for ectoine) hydroxyectoine displays remarkable desiccation protection properties, on a par with sucrose and trehalose. This explains its accumulation in response to increased salinity and elevated temperature by halophiles such as Halomonas elongata and its successful application in ``anhydrobiotic engineering'' of both enzymes and whole cells.
An Event Driven Fusion Approach for Enjoyment Recognition in Real-time

Social signals and interpretation of carried information is of high importance in Human Computer Interaction. Often used for affect recognition, the cues within these signals are displayed in various modalities. Fusion of multi-modal signals is a natural and interesting way to improve automatic classification of emotions transported in social signals. Throughout most present studies, uni-modal affect recognition as well as multi-modal fusion, decisions are forced for fixed annotation segments across all modalities. In this paper, we investigate the less prevalent approach of event driven fusion, which indirectly accumulates asynchronous events in all modalities for final predictions. We present a fusion approach, handling short-timed events in a vector space, which is of special interest for real-time applications. We compare results of segmentation based uni-modal classification and fusion schemes to the event driven fusion approach. The evaluation is carried out via detection of enjoyment-episodes within the audiovisual Belfast Story-Telling Corpus.
VANET: On Mobility Scenarios and Urban Infrastructure. A Case Study

In [1] we show how vehicles can opportunistically exploit infrastructure through open access points (APs) to efficiently communicate with other vehicles. We also highlight the importance of the use of a correct mobility model, since the advantages that may derive from the use of an infrastructure may not be appreciated because of a lack of accuracy. We continue our study based on realistic vehicular mobility traces of downtown Portland, Oregon, obtained from extremely detailed large scale traffic simulations performed at the Los Alamos National Laboratories (LANL). This mobility model is used to evaluate both flat and opportunistic infrastructure routing. We here build upon [1] and extend that work to: (a) assess the impact of a range of mobility models on network performance and; (b) discuss the performance trend we may expect during the day, as urban mobility patterns change. We here compare results obtained with CORSIM [2] traces and Random Waypoint (RWP) [3] to the results obtained with realistic mobility traces.
Multimodal segmentation of object manipulation sequences with product models

In this paper we propose an approach for unsupervised segmentation of continuous object manipulation sequences into semantically differing subsequences. The proposed method estimates segment borders based on an integrated consideration of three modalities (tactile feedback, hand posture, audio) yielding robust and accurate results in a single pass. To this end, a Bayesian approach originally applied by Fearnhead to segment one-dimensional time series data -- is extended to allow an integrated segmentation of multi-modal sequences. We propose a joint product model which combines modality-specific likelihoods to model segments. Weight parameters control the influence of each modality within the joint model. We discuss the relevance of all modalities based on an evaluation of the temporal and structural correctness of segmentation results obtained from various weight combinations.
Capillary versus venous bedside blood glucose estimations

Objectives: To determine the mean difference and correlation between capillary and venous bedside glucose estimation in comparison to laboratory blood glucose analysis in emergency department (ED) patients. Methods: Blood glucose levels were synchronously analysed using a bedside blood glucometer on capillary and venous derived samples from consenting ED patients aged >12 years. The venous sample was sent for comparative testing using a laboratory based multichannel analyser. Mean difference and correlation coefficients were determined. Results: A total of 20 subjects (aged 13–88 years) were enrolled, with 100% data capture. The mean laboratory glucose was 7.075 mmol/l. The mean capillary blood glucose was 7.66 mmol/l (mean difference compared with mean laboratory glucose 0.58 mmol/l; 95% confidence interval 0.3 to 0.9). The mean venous derived blood glucometer glucose was 7.99 mmol/l (mean difference compared with mean laboratory glucose 0.91 mmol/l; 95% CI 0.6 to 1.2). The correlation coefficient for the laboratory blood glucose versus the capillary blood glucometer glucose was 0.97 mmol/l (p<0.001). The correlation coefficient for the laboratory blood glucose and the venous blood glucometer glucose was 0.96 (p<0.001). Variation occurred between the glucometer and the laboratory blood glucose results. Conclusions: There is a small but significant difference in the blood glucose results analysed on a bedside glucometer when the samples are taken from capillary or venous sources. Although good correlation is the norm between venous and capillary derived samples, caution must be exercised in accepting the results as equivalent or using either as substitutes for a laboratory blood glucose result.
Nucleotide sequence of a mouse testis poly(A) binding protein cDNA

The vast majority of eukaryotic mRNAs possess a poly(A) tract at their 3' termini. Although the function of the poly(A) tail is controversial, most workers agree that it promotes mRNA translation and stability (reviewed in 1, 2). The effects of poly (A) on mRNA metabolism are thought to be mediated by a protein which binds preferentially to poly (A), the poly (A) binding protein (PABP) (reviewed in 1, 2). The sequences of PABP cDNAs from yeast (3,4), human (5), Xenopus (6) and Drosophila (7) indicate that PABPs have a conserved structure consisting of 4 repeated RNA binding domains near the amino terminus and a less conserved domain of unknown function at the carboxy terminus. The present study was undertaken to search for testis-specific PABP mRNAs in mice for two reasons. First, haploid spermatogenic cells are an unusual developing system because some translationally active mRNAs have shorter poly(A) tracts than translationally repressed mRNAs (8). Second, there are numerous testis-specific variants of mRNAs which are expressed in somatic cells (reviewed in 9). Two mouse testis cDNA libraries (10, 11) were screened with the 5' proximal EcoRI fragment of human liver PABP cDNA (5) isolating two groups of cDNAs with different sequences. One of these mouse testis PABP cDNAs encodes a 636 amino acid protein which is respectively 98.9% and 94% identical to human and Xenopus PABPs (5, 6) as shown in Figure 1, and 54.9% and 49.5% identical to Drosophila and yeast PABPs (3, 4, 7) (not shown). The slow rate of evolution of mammalian PABPs is noteworthy. Assuming that mice and humans diverged 80 million years ago, the rate of evolution of non-synonymous sites in the mouse and human PABP coding regions can be estimated as 0.035—0.061 substitutions/10 years depending on whether the gap between amino acids 210 and 211 in human is excluded or included (12). The rate of evolution of nonsynonymous sites in mouse and human PABP is the fifth slowest among 36 rodent and human proteins analyzed by Li and Grauer (13). Work is in progress comparing the function and expression of the two PABP mRNAs.
Towards Resilient Geographic Routing in Wireless Sensor Networks

In this paper, we consider the security of geographic forwar ding (GF). In GF, neighbors exchange their location information. Based on the information, a nod e forwards packets to the neighbor that is closest to the destination. Although GF is widely used in ad h oc and wireless sensor networks, its security aspect has rarely been studied. There are a number o f attacks that are possible on GF. In a possible type of attacks, misbehaving nodes can falsify the ir location information. Also, malicious nodes can drop packets that they need to forward towards the destin ation. The first contribution of the paper is to propose a location verification algorithm to address th e attacks falsifying the location information. The second contribution of the paper is to propose approache s for route authentication and trust-based route selection to defeat attacks on GF. We discuss the propo sed approaches in detail, outlining possible attacks and defenses against them. In addition, we show, via simulation, how trust-based route selection is able to circumvent and route against attackers.
Asynchronous Distributed Averaging on Communication Networks

Distributed algorithms for averaging have attracted interest in the control and sensing literature. However, previous works have not addressed some practical concerns that will arise in actual implementations on packet-switched communication networks such as the Internet. In this paper, we present several implementable algorithms that are robust to asynchronism and dynamic topology changes. The algorithms are completely distributed and do not require any global coordination. In addition, they can be proven to converge under very general asynchronous timing assumptions. Our results are verified by both simulation and experiments on Planetlab, a real-world TCP/IP network. We also present some extensions that are likely to be useful in applications.
Writing MOT, Reading AHA! Converting between an authoring and a delivery system for adaptive educational hypermedia

This paper reports about the recent advances towards establishing a common platform for adaptive educational hypermedia (AEH) authoring. We present the conversion from MOT, a dedicated authoring system, to AHA! used in this context as delivery system for AEH. Moreover, we describe two new representation languages that emerged in the process: a common format for defining the static material, CAF, and an extended adaptation language for the description of the dynamic behaviour, LAG. Finally, some evaluations are shown and conclusions are drawn.