Miracle-dz/UniFAR-FTUs huggingface dataset:
Evaluation of the Finnish Diabetes Risk Score (FINDRISC) for diabetes screening in occupational health care.

OBJECTIVES The objective of the study was to investigate the prevalence of undiagnosed dysglycaemia and the risk for type 2 diabetes using the Finnish Diabetes Risk Score (FINDRISC) in the working population of Belgium. Moreover, it was to evaluate performance and applicability of FINDRISC as a screening tool during occupational health surveillance. MATERIAL AND METHODS A cross-sectional analysis was carried out over the years 2010-2011 among 275 healthy employees who underwent a health check including fasting plasma glucose and the FINDRISC questionnaire. The sensitivity, specificity and predictive value of different FINDRISC cut-off values to detect dysglycaemia was revised in the literature and then calculated. RESULTS The prevalence of unknown dysglycaemia was 1.8%. Twelve percent of the employees had a FINDRISC score of 12 to 14 corresponding to a moderate risk of 17% to develop diabetes within the next 10 years, and 5.5% had a score of 15 or more corresponding to a high - very high risk of 33% to 50%. All dysglycaemic individuals had a FINDRISC score of 12 or higher. The sensitivity and specificity for detecting dysglycaemia was respectively 100% and 84.1% for a FINDRISC cut-off value ≥ 12; and 80% and 95.9% for a cut-off value ≥ 15. CONCLUSIONS A considerable number of workers had dysglycaemia or was at risk for developing type 2 diabetes. The questionnaire is a reliable, valuable and easy to use screening tool in occupational health surveillance.
The evolving role of histology in the treatment of non-small cell lung cancer.

Lung cancer is the second most common type of cancer (after prostate in men and breast in women) and a major cause of cancer-related mortality. An estimated 222,520 new cases of lung cancer are expected in 2010, accounting for about 15% of cancer diagnoses. The incidence rate is declining significantly in men, from 102.1 cases in 1984 to 71.3 cases per 100,000 in 2006. In women, the rate is approaching a plateau after a long period of increase. Lung cancer accounts for more deaths than any other cancer in both men and women. An estimated 157,300 deaths, accounting for about 28% of all cancer deaths, are expected to occur in 2010.
Self-reported efficacy of an all in-the-ear-canal prosthetic device to inhibit stuttering during one hundred hours of university teaching: an autobiographical clinical commentary

This manuscript outlines the lifelong battle with severe stuttering and describes a new modality of effective amelioration of the disorder from the standpoint of a university professor and researcher in the field of stuttering. Childhood reactions to stuttering are discussed, along with the educational and vocational impact of stuttering. Ongoing therapy was received throughout the formative years and into adulthood, emphasizing reduced rates of speech. The use of Delayed Auditory Feedback (DAF) was found to induce fluent speech, but was considered only as a tool for decreasing the speech rate to achieve fluency. When fluency under DAF was discovered to be possible at faster speech rates, the possibility that the use of DAF and other forms of altered auditory feedback could themselves have an inhibitory effect on stuttering, without concomitant rate reduction was investigated. An In-The-Canal (ITC) fluency-enhancing device was used that provided DAF and Frequency Altered Feedback (FAF) to produce more fluent speech. After 10 months of use, the author was relatively free from stuttering. Speech was natural sounding, relatively spontaneous and unlaboured with an absence of fear. However, further testing (that is currently underway at various centres) is necessary before generalizations can be made.
[Comparative analysis of soil microbial communities by pyrosequencing and DGGE].

OBJECTIVE We aimed to assess the advantage and disadvantage of next-generation pyrosequencing and traditional Denaturing Gradient Gel Electrophoresis (DGGE) in fingerprinting analysis of soil microbial communities. METHODS We analyzed microbial compositions, abundance and diversity of typical grassland and forest soils by 16S rRNA gene-based pyrosequencing and DGGE to compare the accuracy and reproducibility of the two techniques on soil microbial communities. RESULTS For grassland soils, pyrosequencing technique revealed 22 phyla, 54 classes, 60 orders, 131 families and 350 genera; DGGE only detected 6 phyla, 9 classes, 8.orders, 10 families and 10 genera. The results show that DGGE greatly underestimated soil community compositions. Similar results were obtained for forest soils, and the detection sensitivity of pyrosequencing of forest soils was 3.8, 6.7, 6.4, 19.2 and 39.4 times higher than that of DGGE at the taxonomic levels of phylum, class, order, family and genera respectively. Furthermore, DGGE overwhelmingly overestimated the relative abundance of dominant microorganisms represented by the high-intensity bands, leading up to a 2000-fold difference. Both DGGE and pyrosequencing showed consistent results of microbial diversity changing patterns, although the DGGE-based diversity index was much lower than pyrosequencing. CONCLUSION Pyrosequencing thus provides more comprehensive and accurate fingerprints of soil microbial community structure than DGGE. DGGE only can represent a few numerically dominant phylotypes with apparent overestimation of their relative abundance in soil microbial communities.
An acoustic startle alters knee joint stiffness and neuromuscular control

Growing evidence suggests that the nervous system contributes to non‐contact knee ligament injury, but limited evidence has measured the effect of extrinsic events on joint stability. Following unanticipated events, the startle reflex leads to universal stiffening of the limbs, but no studies have investigated how an acoustic startle influences knee stiffness and muscle activation during a dynamic knee perturbation. Thirty‐six individuals were tested for knee stiffness and muscle activation of the quadriceps and hamstrings. Subjects were seated and instructed to resist a 40‐degree knee flexion perturbation from a relaxed state. During some trials, an acoustic startle (50 ms, 1000 Hz, 100 dB) was applied 100 ms prior to the perturbation. Knee stiffness, muscle amplitude, and timing were quantified across time, muscle, and startle conditions. The acoustic startle increased short‐range (no startle: 0.044 ± 0.011 N·m/deg/kg; average startle: 0.047 ± 0.01 N·m/deg/kg) and total knee stiffness (no startle: 0.036 ± 0.01 N·m/deg/kg; first startle 0.027 ± 0.02 N·m/deg/kg). Additionally, the startle contributed to decreased [vastus medialis (VM): 13.76 ± 33.6%; vastus lateralis (VL): 6.72 ± 37.4%] but earlier (VM: 0.133 ± 0.17 s; VL: 0.124 ± 0.17 s) activation of the quadriceps muscles. The results of this study indicate that the startle response can significantly disrupt knee stiffness regulation required to maintain joint stability. Further studies should explore the role of unanticipated events on unintentional injury.
Ambulatory Recording and Power Spectral Analysis by Autoregressive Modelling of Polygraphic Sleep Signals in Patients Suffering from Chronic Pain

Abstract: A portable digital recording system and the Nightingale sleep analyser have been applied to record polygraphical sleep signals in patients suffering from chronic pain. Using ambulatory recording the patient can sleep at home making the sleep more natural and reducing the costs. The recording system gives digital recordings of very good quality. It is shown that the Nightingale sleep analyser performs automatic sleep analysis with a quality comparable to visual interrater performance on disordered sleep. It furthermore provides means for extraction of spectral information useful for the description of the sleep-wakefulness processes and for diagnosing the sleep disorders. Using AR-model-based power spectral analysis, it is also shown that the power content in the alpha band relative to the delta power is significantly higher in patients suffering from non-specific chronic pain as compared to normal persons.
Convolutional neural network based vehicle turn signal recognition

This Automated driving is an emerging technology in which a car performs recognition, decision making, and control. Recognizing surrounding vehicles is a key technology in order to generate a trajectory of ego vehicle. This paper is focused on detecting a turn signal information as one of the driver's intention for surrounding vehicles. Such information helps to predict their behavior in advance especially about lane change and turn left-or-right on intersection. Using their intension, the automated vehicle is able to generate the safety trajectory before they begin to change their behavior. The proposed method recognizes the turn signal for target vehicle based on mono-camera. It detects lighting state using Convolutional Neural Network, and then calculates a flashing frequency using Fast Fourier Transform.
The role of peptide deformylase in protein biosynthesis: A proteomic study

Recently we investigated the influence of classical and emerging antibiotics on the proteome of Bacillus subtilis including in our studies actinonin, a potent novel inhibitor of peptide deformylase. The protein synthesis pattern under actinonin treatment changed so dramatically that a direct comparison to the control pattern was impossible. Dual channel imaging revealed that actinonin treatment caused the majority of newly synthesised proteins to accumulate in spots different from the ones usually observed, indicating a more acidic isoelectric point. Two strategies were used to investigate the nature of the charge shift. In the first place, protein patterns of a conditional peptide deformylase mutant under nonrepressing and repressing conditions were compared. Secondly, several protein pairs excised from two‐dimensional (2‐D) gels of the peptide deformylase mutant, exponentially growing untreated wild‐type and the actinonin treated wild‐type were investigated with matrix‐assisted laser desorption/ionization and electrospray ionization (ESI) time of flight mass spectrometry (TOF MS) for the existence of N‐terminal formylation. Under nonrepressing conditions the mutant protein pattern resembled that of the wild‐type. The loss of peptide deformylase activity under repressing conditions led to the same pI shift observed for actinonin treatment in the wild‐type. Quadrupole TOF‐MS on 11 protein pairs proved that the remaining N‐terminal formyl residue was indeed responsible for the charge shift. Eight of these protein pairs were also present on 2‐D gels of exponentially growing B. subtilis, where the more acidic, still formylated protein species represented the smaller parts.
Production of anti‐cancer immunotoxins in algae: Ribosome inactivating proteins as fusion partners

The eukaryotic green algae, Chlamydomonas reinhardtii has been shown to be capable of producing a variety of recombinant proteins, but the true potential of this platform remains largely unexplored. To assess the potential of algae for the production of novel recombinant proteins, we generated a series of chimeric proteins containing a single chain antibody (scFv) targeting the B‐cell surface antigen CD22, genetically fused to the eukaryotic ribosome inactivating protein, gelonin, from Gelonium multiflorm. These unique molecules, termed immunotoxins, are encoded as a single gene that produces an antibody—toxin chimeric protein capable of delivering a cytotoxic molecule to targeted B‐cells. We show that the addition of an Fc domain of a human IgG1 to these fusion proteins results in the production of assembled dimeric immunotoxins, containing two cell binding scFvs and two gelonin molecules. Additionally, we demonstrate that these algal expressed proteins are capable of binding and reducing the viability of B‐cell lymphomas, while treatment of T‐cells, that lack the CD22 antigen, had no impact on cell viability. Since other protein expression platforms are incapable of folding and accumulating these complex immunotoxins as soluble and enzymatically active proteins, our studies document a novel and efficient method for immunotoxin production. Biotechnol. Bioeng. 2013;110: 2826–2835. © 2013 Wiley Periodicals, Inc.
Image registration research based on SUSAN-SURF algorithm

Image registration is an important technology of image processing and has a broad application. Good adaptability, computing speed and registration accuracy are the basic requirements in image registration. In recent years, the image registration algorithm based on local invariant features is becoming a hot spot of research, such as the SIFT method is one of them. But the traditional SIFT algorithm has computational complexity and the high real-time performance. SURF algorithm as a new feature extraction method, possess a small amount of calculation and quick speed, but the large amount of feature points are create false match easily. To solve these problems, this paper proposed an effective combination of SUSAN-SURF algorithm, which retain the high efficiency of SURF and the outline information of SUSAN. And then SURF algorithm is effectively improved by using KNN to speed up image matching. Finally the algorithm was verified by experiment, SUSAN-SURF can under the premise in accuracy, improve the real-time performance.
V-Shaped InAs/Al0.5Ga0.5Sb Vertical Tunnel FET on GaAs (001) Substrate With I $_{\text {ON}}=\text {433}\,\,\mu$ A. $\mu$ m $^{-\text {1}}$ at V $_{\text {DS}}= \text {0.5}$ V

We report on the fabrication of a near broken InAs/Al0.5Ga0. 5Sb vertical TUNNEL field effect transistor (TFET). The epitaxial structure is grown on a GaAs (001) substrate thanks to large mismatch accommodation at the GaSb/GaAs interface. The fabrication process involves an anisotropic and selective wet chemical etching of the InAs channel to form a V-shaped mesa with lateral side gates. This new architecture provides a large ON-current at room temperature while enabling an efficient pinch-off thanks to a reduced body thickness near the tunneling interface. With low temperature measurements, we identify the different mechanisms limiting the subthreshold slope at room temperature. At 77 K, where the impact of defects is reduced, a minimum subthreshold slope of 71 mV/decade is achieved for VDS = 0.1 V with an ION/IOFF current ratio larger than 6 decades demonstrating that a good trade-off between ON current and switching efficiency could be obtained with a near broken gap heterostructure based n-TFET.
A Site-specific, Membrane-dependent Cleavage Event Defines the Membrane Binding Domain of FtsY*

Targeting of many polytopic proteins to the inner membrane of prokaryotes occurs via an essential signal recognition particle-like pathway. Unlike the general secretory pathway, the proteins involved in this pathway and their activities appear in many respects to mirror closely those of their eukaryotic homologues. However, the Escherichia coli signal recognition particle receptor, FtsY, differs significantly at the amino terminus from the eukaryote homologue α-subunit of the signal recognition particle receptor. In addition, there is no prokaryote homologue of the transmembrane β-subunit of the receptor. Therefore, FtsY must assemble on the membrane in a unique manner. Using assays designed to accurately discriminate membrane-bound proteins from aggregated material, we found that in contrast to a previous report, only amino acids 1–284 of FtsY are necessary and sufficient for membrane assembly. These amino acids together constitute a bona fidemembrane binding domain that includes both the regions originally designated A and N based on sequence comparisons. Furthermore, we found that a membrane-bound factor mediates specific cleavage of some membrane-bound FtsY molecules between the N and G regions previously believed to be functionally linked to generate a novel membrane-bound isoform composed of only the AN domain.
Weibull partition models with applications to hidden semi-Markov models

We develop the Weibull partition model (WPM), which defines a novel nonparametric stochastic process over distributions of partitions of sequential data, aiming at directly modeling the boundaries of segments comprising the sequence. The Weibull partition model employs a Dirichlet process mixture with a Weibull kernel. Weibull distributions having a closed-form cumulative density function plays an important role in the construction of the Weibull partition model. As an application of our model, we propose the hidden semi-Markov model based on the Weibull partition model (WPM-HSMM), along with the corresponding recursive sampling algorithm. The WPM-HSMM can be used to solve the problem of low accuracy of inference for hidden states, caused by the holding times of hidden states having a complicated distribution. In our experiments, we show that the WPM-HSMM rapidly mixes and achieves very competitive results compared to the state-of-the-art algorithms. Apart from the application to hidden Markov models, the WPM can also be found useful in any problem, where explicitly modeling segment boundaries is needed.
Single-Photon-Added Coherent States of Light Quantum-to-Classical Transition with

www.sciencemag. org (this information is current as of November 30, 2006 ): The following resources related to this article are available online at http://www.sciencemag. org/cgi/content/full/306/5696/660 version of this article at: including high-resolution figures, can be found in the online Updated information and services, http://www.sciencemag. org/cgi/content/full/306/5696/660/DC1 can be found at: Supporting Online Material http://www.sciencemag. org/cgi/content/full/306/5696/660#otherarticles , 1 of which can be accessed for free: cites 6 articles This article 23 article(s) on the ISI Web of Science. cited by This article has been http://www.sciencemag. org/cgi/collection/physics Physics : subject collections This article appears in the following http://www.sciencemag. org/help/about/permissions.dtl in whole or in part can be found at: this article permission to reproduce of this article or about obtaining reprints Information about obtaining
Nanoscale Communication With Molecular Arrays in Nanonetworks

Molecular communication is a promising nanoscale communication paradigm that enables nanomachines to exchange information by using molecules as communication carrier. Up to now, the molecular communication channel between a transmitter nanomachine (TN) and a receiver nanomachine (RN) has been modeled as either concentration channel or timing channel. However, these channel models necessitate exact time synchronization of the nanomachines and provide a relatively low communication bandwidth. In this paper, the Molecular ARray-based COmmunication (MARCO) scheme is proposed, in which the transmission order of different molecules is used to convey molecular information without any need for time synchronization. The MARCO channel model is first theoretically derived, and the intersymbol interference and error probabilities are obtained. Based on the error probability, achievable communication rates are analytically obtained. Numerical results and performance comparisons reveal that MARCO provides significantly higher communication rate, i.e., on the scale of 100 Kbps, than the previously proposed molecular communication models without any need for synchronization. More specifically, MARCO can provide more than 250 Kbps of molecular communication rate if intersymbol time and internode distance are set to 2 μs and 2 nm, respectively.
Dominating and unbounded free sets

Abstract We prove that every analytic set in ωω × ωω with σ-bounded sections has a not σ-bounded closed free set. We show that this result is sharp. There exists a closed set with bounded sections which has no dominating analytic free set. and there exists a closed set with non-dominating sections which does not have a not σ-bounded analytic free set. Under projective determinacy analytic can be replaced in the above results by projective.
TOPLESS Mediates Auxin-Dependent Transcriptional Repression During Arabidopsis Embryogenesis

The transcriptional response to auxin is critical for root and vascular development during Arabidopsis embryogenesis. Auxin induces the degradation of AUXIN/INDOLE-3-ACETIC ACID (AUX/IAA) transcriptional repressors, freeing their binding partners, the AUXIN RESPONSE FACTOR (ARF) proteins, which can activate transcription of auxin response genes. We show that TOPLESS (TPL) can physically interact with IAA12/BODENLOS (IAA12/BDL) through an ETHYLENE RESPONSE FACTOR (ERF)–associated amphiphilic repression (EAR) motif. TPL can repress transcription in vivo and is required for IAA12/BDL repressive activity. In addition, tpl-1 can suppress the patterning defects of the bdl-1 mutant. Direct interaction between TPL and ARF5/MONOPTEROS, which is regulated by IAA12/BDL, results in a loss-of-function arf5/mp phenotype. These observations show that TPL is a transcriptional co-repressor and further our understanding of how auxin regulates transcription during plant development.
Methodology for the evaluation of health information by participants with low literacy skills

This poster presents a case study method developed for a pilot study investigating the evaluation of printand text-based consumer health information by individuals who have low or limited literacy skills in English. The methodology is based on the theory of Everyday Life Information Seeking, usability research, community-based participatory research, and research with vulnerable populations.
A combined estimator for Interferometric SAR ionosphere correction

In recent years, large number of Interferometric SAR applications in earthquake, cryosphere and tectonic geodesy show the great needs for ionospheric effect correction [1-4]. Several approaches, which mainly include the split spectrum InSAR technique, the Faraday rotation based method and the azimuth shift based method (the Multiple Aperture Interferometric and conventional azimuth shift) have been proposed to meet this end [5-11]. These techniques exploit different aspects - phase delay, polarimetric property and geometric distortion of the ionospheric effect on SAR data to retrieve the differential ionosphere in InSAR. These techniques work well in certain conditions, however, their performance might be limited in cases due to noise effect and the weakness of each technique itself. In this study, we are proposing a combined estimator by joining the Faraday rotation based method and the split spectrum technique of InSAR ionospheric effect correction, which is supposed to achieve a more robust and higher accuracy performance comparing to individual technique itself.
The control of arm currents and the parameters for modular multilevel converters

This paper describes the operation of modular multilevel converter (MMC). A control method of adding the feed-forward current is introduced. Another strategy of removing the second harmonic current is also described in order to improve the arm currents. Simulation results based on a detailed PSIM model prove the effectiveness of the two methods. The paper presents principle of parameters selection of MMC especially the arm inductance.