Miracle-dz/UniFAR-FTUs huggingface dataset:
Draft Genome Sequencing and Comparative Analysis of Aspergillus sojae NBRC4239

We conducted genome sequencing of the filamentous fungus Aspergillus sojae NBRC4239 isolated from the koji used to prepare Japanese soy sauce. We used the 454 pyrosequencing technology and investigated the genome with respect to enzymes and secondary metabolites in comparison with other Aspergilli sequenced. Assembly of 454 reads generated a non-redundant sequence of 39.5-Mb possessing 13 033 putative genes and 65 scaffolds composed of 557 contigs. Of the 2847 open reading frames with Pfam domain scores of >150 found in A. sojae NBRC4239, 81.7% had a high degree of similarity with the genes of A. oryzae. Comparative analysis identified serine carboxypeptidase and aspartic protease genes unique to A. sojae NBRC4239. While A. oryzae possessed three copies of α-amyalse gene, A. sojae NBRC4239 possessed only a single copy. Comparison of 56 gene clusters for secondary metabolites between A. sojae NBRC4239 and A. oryzae revealed that 24 clusters were conserved, whereas 32 clusters differed between them that included a deletion of 18 508 bp containing mfs1, mao1, dmaT, and pks-nrps for the cyclopiazonic acid (CPA) biosynthesis, explaining the no productivity of CPA in A. sojae. The A. sojae NBRC4239 genome data will be useful to characterize functional features of the koji moulds used in Japanese industries.
Parsing and evaluating the French Europarl corpus

This paper describes tools and preliminary results from an automatic corpus annotation project. The hybrid Constraint Grammar parser FrAG (Bick 2003 and http://beta.visl.sdu.dk) was run on the French version of the parallel Europarl corpus (http://www.isi.edu/~koehn/europarl/), consisting of 29 million words of original and translated debate transcripts from the European Parliament, and linguistic features were statistically evaluated across the different source languages (SL). The project is part of a larger initiative to create freely accessible and grammatically annotated corpora for French, the FReeBank project (Salmon-Alt et.al. 2004).
Speed Control of Drive Unit in Four-rotor Flying Robot

In this paper the synthesis of speed controller for drive unit is presented. Its aim is to generate the lift force of multi-rotor flying robot. Parameters of drive unit model were experimentally determined based on recorded time characteristics from engine test stand. The use of two alternative controllers: CDM and PID types was proposed. The CDM controller was tuned in accordance with the Coefficient Diagram Method and the PID controller in MATLAB’s Simulink Response Optimization tool. The efficiency of both types control systems was compared for specified conditions. Integral quality indices were adopted as a measure of assessment. Obtained simulation results were discussed in the context of implementation on a real robot.
Determining local natural scales of curves

An alternative to representing curves at a single scale or a fixed number of multiple scales is to represent them only at their natural (i.e. most significant) scales. This allows all the important information concerning the different sized structures contained in the curve to be explicitly represented without the overhead of redundant representations of the curve. This paper describes several approaches to determining the local natural scales of curves. That is, various possibly overlapping sections of the curve should be represented at certain scales depending on their shape. The merits and drawbacks of the techniques are described, and the results of implementing one of them are shown.
Estimation of Energy Expenditure Using a Patch-Type Sensor Module with an Incremental Radial Basis Function Neural Network

Conventionally, indirect calorimetry has been used to estimate oxygen consumption in an effort to accurately measure human body energy expenditure. However, calorimetry requires the subject to wear a mask that is neither convenient nor comfortable. The purpose of our study is to develop a patch-type sensor module with an embedded incremental radial basis function neural network (RBFNN) for estimating the energy expenditure. The sensor module contains one ECG electrode and a three-axis accelerometer, and can perform real-time heart rate (HR) and movement index (MI) monitoring. The embedded incremental network includes linear regression (LR) and RBFNN based on context-based fuzzy c-means (CFCM) clustering. This incremental network is constructed by building a collection of information granules through CFCM clustering that is guided by the distribution of error of the linear part of the LR model.
Expression of a Serine Protease Gene prC Is Up-Regulated by Oxidative Stress in the Fungus Clonostachys rosea: Implications for Fungal Survival

Background Soil fungi face a variety of environmental stresses such as UV light, high temperature, and heavy metals. Adaptation of gene expression through transcriptional regulation is a key mechanism in fungal response to environmental stress. In Saccharomyces cerevisiae, the transcription factors Msn2/4 induce stress-mediated gene expression by binding to the stress response element. Previous studies have demonstrated that the expression of extracellular proteases is up-regulated in response to heat shock in fungi. However, the physiological significance of regulation of these extracellular proteases by heat shock remains unclear. The nematophagous fungus Clonostachys rosea can secret an extracellular serine protease PrC during the infection of nematodes. Since the promoter of prC has three copies of the stress response element, we investigated the effect of environmental stress on the expression of prC. Methodology/Principal Findings Our results demonstrated that the expression of prC was up-regulated by oxidants (H2O2 or menadione) and heat shock, most likely through the stress response element. After oxidant treatment or heat shock, the germination of conidia in the wild type strain was significantly higher than that in the prC mutant strain in the presence of nematode cuticle. Interestingly, the addition of nematode cuticle significantly attenuated the production of reactive oxygen species (ROS) induced by oxidants and heat shock in the wild type strain, but not in prC mutant strain. Moreover, low molecule weight (<3 kD) degradation products of nematode cuticle suppressed the inhibitory effect of conidial germination induced by oxidants and heat shock. Conclusions/Significance These results indicate that PrC plays a protective role in oxidative stress in C. rosea. PrC degrades the nematode cuticle to produce degradation products, which in turn offer a protective effect against oxidative stress by scavenging ROS. Our study reveals a novel strategy for fungi to adapt to environmental stress.
Management of obstructive sleep apnea in pregnant women.

A 32-year-old woman, gravida 6 para 5004, at 37 0/7 weeks of gestation presented for a repeat cesarean delivery. The patient’s pregnancy was complicated by morbid obesity (body mass index [calculated as weight (kg)/[height (m)]2] 53.1), chronic hypertension, and obstructive sleep apnea (OSA) but not pregestational or gestational diabetes. Her antenatal course was uneventful. Her OSA was diagnosed 2 years before this pregnancy but she failed to initiate therapy. A repeat polysomnogram performed at 20 weeks confirmed her OSA with an apnea–hypopnea index of nine events per hour, indicating mild sleep apnea. Her lowest oxygen saturation on the overnight polysomnogram was 76% and she spent 3.9% of her total sleep time with an SpO2 level less than 90%. After multiple visits for evaluation and continuous positive airway pressure (CPAP) adjustment, she initiated CPAP treatment at 12 cm H2O at 26 weeks of gestation. She reported nightly compliance thereafter. The patient underwent an uncomplicated repeat cesarean delivery and a tubal ligation under combined spinal– epidural (12 mg bupivacaine, 20 g fentanyl, 0.2 mg morphine). The neonate weighed 3,148 grams and Apgar scores at 1 and 5 minutes were 9 and 9, respectively. Secondary to our departmental postoperative sleep apnea protocol (Fig. 1), she was monitored on labor and delivery for 24 hours after her cesarean delivery. The patient declined CPAP. Within the first 4 hours postoperatively, the patient was noted to have intermittent hypoxemia with a pulse oximetry nadir of 83%. At that time, her lungs were clear, there was no tachycardia, and she denied chest pain. Therefore, venous thromboembolism or pulmonary edema was deemed unlikely. Subsequently, her pulse oximetry ranged between 93% and 94%. Given her sleep apnea, she was kept on continuous pulse oximetry monitoring for the remainder of her admission. No narcotics beyond the spinal narcotics administered by anesthesia intraoperatively could be administered for the first 24 hours without permission from the anesthesia service (per our neuraxial opioid standing orders). There were no standing orders for opioid medications (intravenous or oral) in the postoperative period beyond 24 hours. Rather, physician assessment of vital signs was required before narcotic administration and ketorolac was used for analgesia. The hypoxemia was most profound in the first 24 hours. On postoperative day 2, her oxygen saturation was consistently approximately 96% with a nadir of 93%. By postoperative day 3, the patient’s pulse oximetry returned back to her preoperative baseline of 98% with no desaturations (on room air). Given her long-standing history of sleep apnea, an echocardiogram was performed to evaluate for the presence of pulmonary hypertension and was noted to be normal. The remainder of the patient’s course was uneventful and she was discharged home on postoperative day 4.
High Time-Resolution Estimation of Multiple Fundamental Frequencies

This paper presents a high time-resolution strategy to estimate multiple fundamental frequencies in musical signals. The signal is first divided into overlapping blocks, and a high-resolution estimate made of the short-term spectrum. The resulting spectrum is modified such that only the most relevant spectral components are considered, and an iterative algorithm based on earlier work by Klapuri is used to identify candidate fundamental frequencies. Finally, a context-based rule is used to improve the accuracy of fundamental frequency estimates. The performance of this technique is investigated under both noiseless and noisy conditions, and its accuracy is examined in cases where the polyphony is known and unknown a priori.
An Exploratory Study of Residents’ Perception of Place Image

Studies on place image have predominantly focused on the tourists’ destination image and have given limited attention to other stakeholders’ perspectives. This study aims to address this gap by focusing on the notion of residents’ place image, whereby it reviews existing literature on residents’ place image in terms of whether common attributes can be identified, and examines the role of community-focused attributes in its measurement. Data collected from a sample of 481 Kavala residents (Greece) were subjected to exploratory and confirmatory factor analysis. The study reveals that the existing measurement tools have typically emphasized destination-focused attributes and neglected community-focused attributes. This study contributes to the residents’ place image research by proposing a more holistic measurement, which consisted of four dimensions: physical appearance, community services, social environment, and entertainment opportunities. The study also offers practical insights for developing and promoting a tourist place while simultaneously enhancing its residents’ quality of life.
A method based on the granger causality and graph kernels for discriminating resting state from attentional task

Exploring the directional connections between brain regions is of great importance in understanding the brain function. As a method of this exploration, Granger causality is defined in terms of the amount of improvement in the estimation of a signal by past samples of another signal (cause). This method produced reliable results in various applications. In current study, we use connections of directed graphs as the features for discriminating two brain states, rest and attentional cueing task, in a block design fMRI dataset. We apply a support vector machine (SVM) which is enriched by graph kernels like random walk, graphlet and sub-tree kernels on directed graphs of different brain states. Graph kernel methods are a branch of graph matching methods and have recently been proposed as a theoretically sound and promising approach to the problem of graph comparison. They measure the inexact similarity between graphs. For the first time, we apply graph kernels on graphs of brain's effective connectivity. We achieved classification accuracy of 100% in discrimination of resting state from attentional task. We also obtain one graph for each brain state representing causal connections between brain regions. From the networks obtained for each state, we can infer that caudate is the source of information in both states and Left ventromedial prefrontal is the sink of information in the resting state.
Studies on photocatalytic degradation of polystyrene

Abstract This paper reports the photo degradation of polystyrene (PS) by using zinc oxide (ZnO) as photo catalyst. Virgin PS is not responsive to degradation by ultra violet (UV) light because of the presence of phenyl rings in its repeating units. ZnO acts as an UV absorber and helps in transferring the absorbed energy to various bonds of PS and causes degradation. The concentration of ZnO followed by the dispersion within the PS matrix has been found to be the key as the maximum weight loss of ∼ 16% in 2 h has been obtained with 0·5 wt-% of ZnO. Below and above this concentration, the degradation is clearly low. Addition of a UV sensitive dye has further improved this degradation (up to 18%) owing to synergism with ZnO. The degradation of PS has been further highlighted from infrared spectroscopy, surface analysis, viscosity average molecular weight studies and mechanical properties analysis. A suitable mechanism supporting the UV degradation has also been proposed.
Protein Sequences Classification Based on String Weighting Scheme

We present a new technique to recognize remote protein homologies that rely on combining probabilistic modeling and supervised learning in high-dimensional feature spaces. The main novelty of our technique is the method of constructing feature vectors using Hidden Markov Model and the combination of this representation with a classifier capable of learning in very sparse high-dimensional spaces. Each feature vector records the sensitivity of each protein domain to a previously learned set of sub-sequences (strings). Unlike other previous methods, our method takes in consideration the conserved and nonconserved regions. The system subsequently utilizes Support Vector Machines (SVM) classifiers to learn the boundaries between structural protein classes. Experiments show that this method, which we call the String Weighting Scheme-SVM (SWS-SVM) method, significantly improves on previous methods for the classification of protein domains based on remote homologies. Our method is then compared to five existing homology detection methods.
Analytical Derivation of the AC-Side Input Admittance of a Modular Multilevel Converter With Open- and Closed-Loop Control Strategies

This paper deals with the derivation of the ac-side input admittance of a grid-connected modular multilevel converter (MMC) under both open- and closed-loop ac-side current control strategies. The contribution of the internal dynamics of the MMC on the input admittance depends on the type of ac-side controllers implemented. For this reason, the input admittance is first derived with the MMC operating in open loop on the ac side. The results are then modified to include various ac-side controllers in order to analyze the impact of the internal dynamics of the MMC on the total input admittance. Based on the findings, recommendations are given on modeling the input admittance of the MMC. Finally, the derived analytical models are verified using a detailed switching model of the MMC in the frequency domain.
Tunable Fabry-Pérot cavities fabricated from PECVD silicon nitride employing zinc sulphide as the sacrificial layer

The construction of self-supporting and suspended structures is one of the fundamental challenges of microelectromechanical systems (MEMS). Many technologies have been developed for the fabrication of such structures, which can be categorized into bulk or surface micromachining. Generally surface micromachining techniques rely on a high-temperature deposition process such as low pressure chemical vapour deposition to produce high-quality films. Plasma enhanced chemical vapour deposition (PECVD) can be used to deposit films at temperatures less than 300? C. PECVD of silicon nitride has not been used extensively in MEMS structures due to the material limitations created via the deposition technique, primarily controllability of the intrinsic stress and etch selectivity of the deposited film. We show here that PECVD silicon nitride can be used successfully in MEMS structures, and that the intrinsic stress is controllable through variations in the PECVD deposition parameters. A MEMS-based Fabry-P? rot cavity has been fabricated using PECVD silicon nitride as the membrane layer with ZnS as the sacrificial material. Devices with an initial 1? m cavity length typically provide a displacement of 240? nm across a 380? m membrane span for an applied bias of only 1.6? V.
Submodular Maximization with Cardinality Constraints

We consider the problem of maximizing a (non-monotone) submodular function subject to a cardinality constraint. In addition to capturing well-known combinatorial optimization problems, e.g., Max-k-Coverage and Max-Bisection, this problem has applications in other more practical settings such as natural language processing, information retrieval, and machine learning. In this work we present improved approximations for two variants of the cardinality constraint for non-monotone functions. When at most k elements can be chosen, we improve the current best 1/e -- o(1) approximation to a factor that is in the range [1/e + 0.004, 1/2], achieving a tight approximation of 1/2 -- o(1) for k = n/2 and breaking the 1/e barrier for all values of k. When exactly k elements must be chosen, our algorithms improve the current best 1/4 -- o(1) approximation to a factor that is in the range [0.356, 1/2], again achieving a tight approximation of 1/2 -- o(1) for k = n/2. Additionally, some of the algorithms we provide are very fast with time complexities of O(nk), as opposed to previous known algorithms which are continuous in nature, and thus, too slow for applications in the practical settings mentioned above. Our algorithms are based on two new techniques. First, we present a simple randomized greedy approach where in each step a random element is chosen from a set of "reasonably good" elements. This approach might be considered a natural substitute for the greedy algorithm of Nemhauser, Wolsey and Fisher [45], as it retains the same tight guarantee of 1--1/e for monotone objectives and the same time complexity of O(nk), while giving an approximation of 1/e for general non-monotone objectives (while the greedy algorithm of Nemhauser et. al. fails to provide any constant guarantee). Second, we extend the double greedy technique, which achieves a tight 1/2 approximation for unconstrained submodular maximization, to the continuous setting. This allows us to manipulate the natural rates by which elements change, thus bounding the total number of elements chosen.
Sequence Variation and Expression Analysis of Seed Dormancy- and Germination-Associated ABA- and GA-Related Genes in Rice Cultivars

Abscisic acid (ABA) and Gibberellic acid (GA) play key roles in regulating seed dormancy and germination. First, when examining germination of different rice cultivars, we found that their germination timing and dormancy status are rather distinct, coupled with different GA/ABA ratio. Second, we studied genomic sequences of ABA and GA dormancy- and germination-associated genes in rice and discovered single nucleotide polymorphisms and insertions/deletions (Indels) in both coding and regulatory sequences. We aligned all these variations to the genome assemblies of 9311 and PA64s and demonstrated their relevance to seed dormancy both quantitatively and qualitatively based on gene expression data. Third, we surveyed and compared differentially expressed genes in dry seeds between 9311 and PA64s to show that these differentially expressed genes may play roles in seed dormancy and germination.
CAIPIRINHA-VIBE and GRAPPA-VIBE for Liver MRI at 1.5 T: A Comparative In Vivo Patient Study

Objective Three-dimensional T1-weighted (T1W) gradient recall echo volumetric interpolated breath-hold examination (VIBE) using generalized autocalibrating partially parallel acquisitions (GRAPPA) is one of the key sequences in liver magnetic resonance imaging (MRI) and is used for precontrast, dynamic postcontrast, and delayed postcontrast imaging. The purpose of this study is to compare image quality and liver lesion detection (LLD) on a shorter-duration T1W VIBE sequence using the controlled aliasing in parallel imaging results in higher acceleration (CAIPIRINHA) technique with the conventional T1W GRAPPA-VIBE sequence during a single liver MRI session on a 1.5-T Seimens scanner. Methods Twenty consecutive patients (9 women and 11 men; age range, 36–85 years) were included in this prospective study. All patients underwent a complete liver MRI on a 1.5-T magnet (Aera; Siemens Medical Systems, Erlangen, Germany) that consisted of a T1W (in/out-of-phase), T2W, DWI, and precontrast and postcontrast multiphasic images (late arterial, 50 seconds, 120 seconds, and 300 seconds) with GRAPPA-VIBE. The CAIPI-VIBE images were acquired for precontrast and at 300 seconds (5 minutes) postcontrast phases (6.9 seconds per phase) in addition to GRAPPA-VIBE (21 seconds per phase). The shorter time for the CAIPI-VIBE was selected to allow postprocessing of image acquisition in the setting of multi–late arterial phase (single breath hold) postcontrast images. Five radiologists independently analyzed image quality with predefined scores for liver edge sharpness, artifacts, fat saturation deficiency, visualization of the portal veins and hepatic veins, and LLD (size, <0.5–3.8 cm). Score 0 was suboptimal (inadequate), 1 was acceptable for diagnosis, and 2 was optimal (excellent). Kappa statistics were used to assess agreement among readers. Generalized linear mixed model with generalized estimation equation method was used to estimate and compare the LLD failure rates. Results No statistically significant difference was seen in the degree of reader variability between CAIPI-VIBE and GRAPPA-VIBE for all evaluated categories using multirater &kgr; statistics. For the precontrast and 5-minutepostcontrast phase sequences, greater than 95% of images were considered to be of acceptable quality in all image quality categories for both sequences. Forty-one lesions were evaluated in 17 patients with total of 204 observations (n = 204) by 5 readers. For 5-minute postcontrast images, the LLD rate of CAIPI-VIBE (80%) was lower than GRAPPA-VIBE (84%) (P = 0.03) for small lesions (0.5–1.7 cm). There was no significant difference in lesion detection on precontrast images. Conclusions At 1.5 T, the CAIPI-VIBE may be helpful in reducing scan time and demonstrates similar image quality compared with the traditional GRAPPA-VIBE. The CAIPI-VIBE has shorter breath-hold time requirement and thus can be an acceptable alternative for the precontrast and 5-minute postcontrast GRAPPA-VIBE in patients with breath-hold difficulties.