Miracle-dz/UniFAR-FTUs huggingface dataset:
Restriction of interferon gamma responsiveness and basal expression of the myeloid human Fc gamma R1b gene is mediated by a functional PU.1 site and a transcription initiator consensus

The restricted expression of the human Fc gamma R1b gene to myeloid cells is likely to be regulated by a combination of transcription factors that may not be solely expressed in myeloid cells, but act together to restrict the expression of the gene to myeloid cells. Low basal expression of the human Fc gamma R1b gene is specifically upregulated by interferon gamma (IFN-gamma). A 181-bp region of 5' flanking sequence contains several key regulatory motifs that include the extended gamma response region (XGRR) and the PIE region. The XGRR contains the 39-bp gamma response region originally defined in the highly homologous Fc gamma R1a gene. The XGRR is in close proximity to the 21-bp PIE motif that is conserved in the promoters of some other myeloid genes. The PIE motif contains a consensus site for the macrophage and B cell transcription factor, PU.1, and is adjacent to the cluster of transcription start sites. An active transcription initiator, Inr, consensus spans the start sites and appears to direct transcription initiation of this TATA-less gene. In this study, we demonstrate that the PIE region contains a functional PU.1 site that binds a human PU.1-like protein and that associated factors present in myeloid extracts also bind in this PIE region. Mutational analysis reveals an absolute requirement for an intact PU.1 box for both basal and IFN-gamma inducible expression of this gene. In addition, mutations in the Inr greatly reduce basal and inducible transcription. Insertion of a strong TATA box downstream from the Inr or at -30 bp from the transcription start sites restores basal and inducible activity in the presence of a mutated PU.1 site. We also demonstrate that indeed, when the XGRR is positioned in the context of a heterologous TATA containing promoter, it is able to respond equivalently to either IFN-alpha or IFN- gamma. However, IFN-alpha responsiveness does not occur in the context of the physiological Fc gamma R1b TATA-less basal promoter. Our results suggest that a human PU.1-like factor acts as a "bridging factor" between the upstream IFN-gamma enhancer and the Inr dependent preinitiation complex. These findings indicate that the structure of the basal promoter in combination with restricted activators like PU.1 are important in regulating the expression of this gene.
A developmental context for multiple genetic alterations in Wilms’ tumor

SUMMARY Wilms’ tumor has served as an example of Knudson’s two-hit hypothesis of recessive tumor genes, but the genetics has proven to be surprisingly complex. WT1, a tumor suppressor gene on 11p13, is mutated in only a small fraction of Wilms’ tumors, and a second chromosomal region, 11p15, harbors a second Wilms’ tumor gene also involved in other cancers. In addition, loss of genomic imprinting, or parental origin-specific gene expression of at least two genes, appears to be an early step in Wilms’ tumorigenesis and common cancers. Finally, genes on other chromosomes also play a role. I propose a model of Wilms’ tumorigenesis in which multiple genetic alterations act within a specific developmental context, accounting for the epidemiological and pathological heterogeneity of Wilms’ tumor, as well as the tissue specificity of the tumor types arising from alterations in these genes.
Analysis of discontinuous PWM strategies of three-level inverters (I)

In the area of high voltages and powers, the high quality inverter-fed ac drive is more easily achieved by the use of three-level inverters. For three-level inverters three different PWM control regions can be introduced where different two-phase (discontinuous) PWM strategies may be applied. This paper deals with the analysis of voltage spectra of one discontinuous PWM method of three-level inverters when every 60deg of each fundamental period the one motor phase is clamped to dc bar. The derivation of the analytical equations of motor voltage harmonics for this PWM method is given for both realizations: with one and with two carrier waves. The comparison of the voltage spectra of the possible PWM methods is presented. It is shown that in the low voltage area the same value of motor harmonic losses are produced for both one and two carrier wave solutions. However, for the high voltage area the harmonic losses associated with the two carrier modulation are usually considerably lower than in case of one carrier method. The two carrier method can be disadvantageous only for low modulation frequency when the low order harmonics reach the sensitive value
Probabilistic estimation of temporary lanes at road work zones

Road work zones pose a great challenge for the environmental perception with sensors and the correct modelling of the scenery. Especially the recognition of the valid lane is of great interest for driver assistance systems. At road work zones temporary lanes invalidate the original lanes while the latter are still present on the road. All lines are detected with a greyscale video camera. In this paper we present an approach which generates different hypotheses for the lanes originated from the two different types of lines. A particle filter is applied for smoothing and filtering while a JIPDA algorithm is used for association and with its existence estimation helps to find the most plausible hypothesis of the currently valid lane.
Service Substitution Revisited

In this paper, we propose a framework that reduces the complexity of service substitution. The framework is based on two substitution relations and corresponding theorems. The proposed relations and theorems allow organizing available services into groups. Then, the complexity of retrieving candidate substitute services for the target service and generating corresponding adapters scales up with the number of available groups, instead of scaling up with the number of available services.
Retraction Note to: “A uniqueness lemma with applications to regularization and incompressible fluid mechanics”

In this paper, we extend our previous result from [16]. We prove that transport equations with rough coefficients do possess a uniqueness property. Our method relies strongly on duality and bears a strong resemblance with the well-known DiPerna-Lions theory first developed in [8]. As an application, we show a uniqueness result for the Euler and Navier-Stokes equations at the Leray regularity scale. In turn, this theorem stands as a barrier against the paradoxical weak solutions constructed in [17], [18], [19] and later reformulated in [6].
Comment on "Maximum likelihood decoding of uncoded and coded PSK signal sequences transmitted over Rayleigh flat-fading channels"

This comment points out some papers published before the paper of Vitetta and Taylor (see ibid., vol.43, no.11, p.2750-58, 1995). These early papers have dealt with the general problem of maximum-likelihood sequence estimation of coded/uncoded phase-shift keying (PSK) and quadrature amplitude modulation (QAM) signals in correlated Rician and Rayleigh-fading channels. These publications did not assume use of interleaving or use of optimal codes, designed for interleaved systems. The statistical properties of the multiplicative fading process have been included in the design of the receivers which were proposed, analyzed, and evaluated. The research contributions documented in these papers have also shown for the first time in the open literature the link between conventional detection techniques and the maximum-likelihood detection of signals in this type of fading channels.
Estimating the information rate of a channel with classical input and output and a quantum state

We consider the problem of transmitting classical information over a time-invariant channel with memory. A popular class of time-invariant channels with memory are finite-state-machine channels, where a classical state evolves over time and governs the relationship between the classical input and the classical output of the channel. For such channels, various techniques have been developed for estimating and bounding the information rate. In this paper we consider a class of time-invariant channels where a quantum state evolves over time and governs the relationship between the classical input and the classical output of the channel. We propose algorithms for estimating and bounding the information rate of such channels. In particular, we discuss suitable graphical models for doing the relevant computations.
Model-based dereverberation in the logmelspec domain for robust distant-talking speech recognition

The REMOS (REverberation MOdeling for Speech recognition) concept for reverberation-robust distant-talking speech recognition, introduced in [1] for melspectral features, is extended in this contribution to logarithmic melspectral (logmelspec) features. Based on a combined acoustic model consisting of a hidden Markov model network and a reverberation model, REMOS determines clean-speech and reverberation estimates during recognition by an inner optimization operation. A reformulation of this inner optimization problem for logmelspec features, allowing an efficient solution by nonlinear optimization algorithms, is derived in this paper so that an efficient implementation of REMOS for logmelspec features becomes possible. Connected digit recognition experiments show that the proposed REMOS implementation significantly outperforms reverberantly-trained HMMs in highly reverberant environments.
Fate of organochlorine 14C-dicofol in a lab-scale wastewater treatment

The fate of organochlorine 14C-dicofol in activated sludge process was investigated. Results showed that the major part of radioactivity remained adsorbed on biological sludge. Consequently, its final disposal deserves special attention. The small amounts of dicofol, biotransformed or not, which remained in the treated effluent could contaminate receiving bodies.
Biochemical Characterization of the Methanothermobacter thermautotrophicus Minichromosome Maintenance (MCM) Helicase N-terminal Domains*

Minichromosome maintenance helicases are ring-shaped complexes that play an essential role in archaeal and eukaryal DNA replication by separating the two strands of chromosomal DNA to provide the single-stranded substrate for the replicative polymerases. For the archaeal protein it was shown that the N-terminal portion of the protein, which is composed of domains A, B, and C, is involved in multimer formation and single-stranded DNA binding and may also play a role in regulating the helicase activity. Here, a detailed biochemical characterization of the N-terminal region of the Methanothermobacter thermautotrophicus minichromosome maintenance helicase is described. Using biochemical and biophysical analyses it is shown that domain C of the N-terminal portion, located adjacent to the helicase catalytic domains, is required for protein multimerization and that domain B is the main contact region with single-stranded DNA. It is also shown that although oligomerization is not essential for single-stranded DNA binding and ATPase activity, the presence of domain C is essential for helicase activity.
Parallel K-Means Clustering for Gene Expression Data on SNOW

The exponential growth in the amount of data brings in new challenges for data analysis. Gene expression dataset is one such type of data necessitating analytical methods to mine patterns implicit in it. Although clustering has been a popular way to analyze such dataset, the increase in size of dataset necessitates the need for improving the efficiency of clustering methods. In this paper, we study the use of using Principal Components (PCs) as a pre-processing step to provide a more efficient data structure to a parallel formulation of the sequential K-Means algorithm, utilizing multiple cores available in a desktop computer, via the Simple Network of Workstations (SNOW) package. Initial result suggests that SNOW package provides an intuitive way for biologists to parallelize algorithms and speedup job execution, particularly for jobs like K-Means clustering which depends on random starting centroid locations.
Transport pathways of peroxyacetyl nitrate in the upper troposphere and lower stratosphere from different monsoon systems during the summer monsoon season

Abstract. The Asian summer monsoon involves complex transport patterns with large-scale redistribution of trace gases in the upper troposphere and lower stratosphere (UTLS). We employ the global chemistry–climate model ECHAM5–HAMMOZ in order to evaluate the transport pathways and the contributions of nitrogen oxide species peroxyacetyl nitrate (PAN), NOx and HNO3 from various monsoon regions, to the UTLS over southern Asia and vice versa. Simulated long-term seasonal mean mixing ratios are compared with trace gas retrievals from the Michelson Interferometer for Passive Atmospheric Sounding aboard ENVISAT(MIPAS-E) and aircraft campaigns during the monsoon season (June–September) in order to evaluate the model's ability to reproduce these transport patterns. The model simulations show that there are three regions which contribute substantial pollution to the South Asian UTLS: the Asian summer monsoon (ASM), the North American monsoon (NAM) and the West African monsoon (WAM). However, penetration due to ASM convection reaches deeper into the UTLS compared to NAM and WAM outflow. The circulation in all three monsoon regions distributes PAN into the tropical latitude belt in the upper troposphere (UT). Remote transport also occurs in the extratropical UT where westerly winds drive North American and European pollutants eastward where they can become part of the ASM convection and lifted into the lower stratosphere. In the lower stratosphere the injected pollutants are transported westward by easterly winds. Sensitivity experiments with ECHAM5–HAMMOZ for simultaneous NOx and non-methane volatile organic compounds (NMVOCs) emission change (−10 %) over ASM, NAM and WAM confirm similar transport. Our analysis shows that a 10 % change in Asian emissions transports ~ 5–30 ppt of PAN in the UTLS over Asia, ~ 1–10 ppt of PAN in the UTLS of northern subtropics and mid-latitudes, ~ 7–10 ppt of HNO3 and ~ 1–2 ppb of ozone in UT over Asia. Comparison of emission change over Asia, North America and Africa shows that the highest transport of HNO3 and ozone occurs in the UT over Asia and least over Africa. The intense convective activity in the monsoon regions is associated with lightning and thereby the formation of additional NOx. This also affects the distribution of PAN in the UTLS. Simulations with and without lightning show an increase in the concentrations of PAN (~ 40 %), HNO3 (75 %), NOx (70 %) and ozone (30 %) over the regions of convective transport. Lightning-induced production of these species is higher over equatorial Africa and America compared to the ASM region. This indicates that the contribution of anthropogenic emissions to PAN in the UTLS over the ASM is higher than that of lightning.
Group Secret Key Generation via Received Signal Strength: Protocols, Achievable Rates, and Implementation

Secret key generation among wireless devices using physical layer information of radio channel has been an attractive alternative for ensuring security in mobile environments. Received signal strength (RSS) based secret key extraction gains much attention due to its easy accessibility in wireless infrastructure. However, the problem of using RSS to generate keys among multiple devices to ensure secure group communication in practice remains open. In this work, we propose a framework for collaborative key generation among multiple wireless devices leveraging RSS. To deal with mobile devices not within each other's communication range, we employ relay nodes to achieve reliable key extraction. To enable secure group communication, two protocols are developed to perform collaborative group key generation via star and chain topologies respectively. We further provide the theoretic analysis on the achievable secrecy rate for both star and chain topologies in the presence of an eavesdropper. Our prototype development using MICAz motes and extensive experiments using fading trend based key extraction demonstrate the feasibility of using RSS for group key generation in both indoor and outdoor environments, and concurrently achieving a lower bit mismatch rate compared to existing studies.
Sentiment Analysis of Occupy Wall Street Tweets

THE rise of social media has changed political discourse around the world by extending the potential reach of otherwise marginal voices and creating opportunities for massive group coordination and action. The ”Arab Spring” protest movements of the past year demonstrate the political power of these tools. A survey by a news organization in the region reported that the “vast majority of . people surveyed over three weeks in March said they were getting their information from social media sites (88 per cent in Egypt and 94 per cent in Tunisia)” [5]. As the Twitter stream becomes richer in information and more significant in political impact, the value of monitoring and understanding the stream increases. The United States’ Department of Homeland Security, for example, recently announced its intention to develop a system for collecting intelligence information from Twitter and Facebook [2]. The immense quantity of the data available makes identifying key trends non-trivial, however, as Department of Homeland Security Undersecretary Carolyn Wagner comments: “We’re still trying to figure out how you use things like Twitter as a source . How do you establish trends and how do you then capture that in an intelligence product? ” Human observers, inundated by thousands of tweets, need computational tools to aid them in analysis of social media data. While application programming interfaces allow easy automated collection of large social media datasets, analysis of these datasets remains difficult. Simple keyword searches can help identify topics discussed in social media posts, but much of the value of these data lies in the posters’ opinions about these topics, encoded in their messages but difficult to extract computationally. Fortunately, machine learning offers a potential solution through the field of sentiment analysis. A sentiment analysis algorithm “seeks to identify the viewpoint(s) underlying a text span” [8] by extracting descriptive features from text fragments and using them as inputs to a learned hypothesis function. Such algorithms have already been used to classify opinions on current events as expressed in news sources [4]. Asur and Huberman applied sentiment analysis to Twitter data to forecast box-office revenue for movies with competitive accuracy [1]. By training such an algorithm to recognize specific political sentiments of interest rather than opinions about movies, an observer could “predict the future” of relevant political movements much as Asur and Huberman predicted market behavior [1]. In this investigation we apply machine learning methods to analysis of political sentiment in social media. We concentrate on a specific political phenomenon, the Occupy Wall Street movement, and a particular social media platform, Twitter.com. Furthermore, we restrict ourselves to classifying postings into three categories: pro-OccupyWall-Street, anti-Occupy-Wall-Street, and neutral or unrelated. We apply a series of machine learning techniques to these data.
Petri nets state space analysis in the cloud

Several techniques for addressing the state space explosion problem in model checking have been studied. One of these is to use distributed memory and computation for storing and exploring the state space of the model of a system. In this report, we present and compare different multi-thread, distributed, and cloud approaches to face the state-space explosion problem. The experiments report shows the convenience (in particular) of cloud approaches.
Prospective study of C-reactive protein and the risk of future cardiovascular events among apparently healthy women.

BACKGROUND C-reactive protein (CRP) predicts risk of myocardial infarction (MI) and stroke among apparently healthy men, but in women, virtually no data are available. METHODS AND RESULTS CRP was measured in baseline blood samples from 122 apparently healthy participants in the Women's Health Study who subsequently suffered a first cardiovascular event and from 244 age- and smoking-matched control subjects who remained free of cardiovascular disease during a 3-year follow-up period. Women who developed cardiovascular events had higher baseline CRP levels than control subjects (P=0.0001), such that those with the highest levels at baseline had a 5-fold increase in risk of any vascular event (RR=4.8; 95% CI, 2.3 to 10.1; P=0.0001) and a 7-fold increase in risk of MI or stroke (RR=7.3; 95% CI, 2.7 to 19.9; P=0.0001). Risk estimates were independent of other risk factors, and prediction models that included CRP provided a better method to predict risk than models that excluded CRP (all P values <0.01). In stratified analyses, CRP was a predictor among subgroups of women with low as well as high risk as defined by other cardiovascular risk factors. CONCLUSIONS In these prospective data among women, CRP is a strong independent risk factor for cardiovascular disease that adds to the predictive value of risk models based on usual factors alone. (Circulation. 1998;98:731-733.)
Secured data storage on cloud systems via wavefront multiplexing

Security on data storage and transport are among many important concerns on cloud computing. Wavefront multiplexing/demultiplexing process (WF muxing/demuxing) embodying an architecture that utilizes multi-dimensional transmissions is the use of an algorithm for satellite and deep-space communications where transmissions demand a high degree of power combining, security, reliability, and optimization. It has found applications in fields beyond communications domain. One such application is data storage and transport on cloud. Multiple data sets are preprocessed by a WF muxing transformation before being stored /transported. WF muxed data is aggregated data from multiple data sets that have been “customized processed” and disassembled into any scalable number of sets of processed data, with each set being stored on a storage site. The original data is reassembled via a WF demuxing transformation after retrieving a lesser but scalable number of WF muxed data sets. In short, the WF muxed data storage solution enhances data security and data redundancy by, respectively, creating a new dimension to existing security/privacy methods and significantly reducing the storage space needed for data redundancy. In addition, WF muxing/demuxing methods enable a monitoring capability on the integrity of stored data. It becomes possible to identify independently whether the stored data is not contaminated or altered without scrutinizing through the data sets themselves.
Semi-Automatic Ontology Merging of Domain Specific Ontologies

: Ontologies aim at providing a formal, explicit and shared conceptualization and understanding of common domains between different communities. However, the distributed nature of ontology development resulted in the semantic heterogeneity between ontologies. Semantic heterogeneity constitutes the major obstacle against achieving interoperability between ontologies. To overcome this obstacle a novel method is designed for semi-automatic ontology merging. It combines syntactic and semantic measures for identifying similar concepts that will be merged in a signal one in the resulting merged ontology. The structural relationships between ontologies are solved by similarity measures. After combining the results, similar concepts are merged in a single one by normalizing the weights of all the similarity measures.