Miracle-dz/UniFAR-FTUs huggingface dataset:
Proteomic and Biochemical Changes during Senescence of Phalaenopsis ‘Red Dragon’ Petals

Phalaenopsis flowers are some of the most popular ornamental flowers in the world. For most ornamental plants, petal longevity determines postharvest quality and garden performance. Therefore, it is important to have insight into the senescence mechanism of Phalaenopsis. In the present study, a proteomic approach combined with ultrastructural observation and activity analysis of antioxidant enzymes was used to profile the molecular and biochemical changes during pollination-induced petal senescence in Phalaenopsis “Red Dragon”. Petals appeared to be visibly wilting at 24 h after pollination, accompanied by the mass degradation of macromolecules and organelles during senescence. In addition, 48 protein spots with significant differences in abundance were found by two-dimensional electrophoresis (2-DE) and subjected to matrix-assisted laser desorption/ionization time of flight mass spectrometry (MALDI-TOF/TOF-MS). There were 42 protein spots successfully identified and homologous to known functional protein species involved in key biological processes, including antioxidant pathways, stress response, protein metabolism, cell wall component metabolism, energy metabolism, cell structure, and signal transduction. The activity of all reactive oxygen species (ROS)-scavenging enzymes was increased, keeping the content of ROS at a low level at the early stage of senescence. These results suggest that two processes, a counteraction against increased levels of ROS and the degradation of cellular constituents for maintaining nutrient recycling, are activated during pollination-induced petal senescence in Phalaenopsis. The information provides a basis for understanding the mechanism regulating petal senescence and prolonging the florescence of Phalaenopsis.
Improving melody extraction using Probabilistic Latent Component Analysis

We propose a new approach for automatic melody extraction from polyphonic audio, based on Probabilistic Latent Component Analysis (PLCA). An audio signal is first divided into vocal and non-vocal segments using a trained Gaussian Mixture Model (GMM) classifier. A statistical model of the non-vocal segments of the signal is then learned adaptively from this particular input music by PLCA. This model is then employed to remove the accompaniment from the mixture, leaving mainly the vocal components. The melody line is extracted from the vocal components using an auto-correlation algorithm. Quantitative evaluation shows that the new system performs significantly better than two existing melody extraction algorithms for polyphonic single-channel mixtures.
Variational Gaussian-process factor analysis for modeling spatio-temporal data

We present a probabilistic factor analysis model which can be used for studying spatio-temporal datasets. The spatial and temporal structure is modeled by using Gaussian process priors both for the loading matrix and the factors. The posterior distributions are approximated using the variational Bayesian framework. High computational cost of Gaussian process modeling is reduced by using sparse approximations. The model is used to compute the reconstructions of the global sea surface temperatures from a historical dataset. The results suggest that the proposed model can outperform the state-of-the-art reconstruction systems.
Patient weighting of importance of asthma symptoms

BACKGROUND Quality of life measures are increasingly important in evaluating outcomes in asthma. If some asthma symptoms are more troublesome to patients than others, this may affect their contribution to outcome measures. This study was designed to assess the relative importance of common symptoms in adults with asthma. METHODS A postal survey using conjoint analysis was performed in 272 adults attending hospital outpatient clinics with moderately severe asthma. Patients were asked to chose between “symptom scenarios” offering different combinations of levels of five common asthma symptoms over one week. Two versions of the questionnaire were used with identical scenarios presenting symptoms in different orders. Different patients answered the two versions. Regression analysis was used to calculate symptom weights for daytime cough, breathlessness, wheeze and chest tightness, and sleep disturbance. RESULTS Symptom order, percentage predicted peak expiratory flow (PEF), and symptoms in the week before the survey did not influence the choice of scenario. In both questionnaires patients were more likely to choose scenarios with low levels of cough and breathlessness than low sleep disturbance, wheeze or chest tightness. Regression weights for cough (–0.52) and breathlessness (–0.49) were twice those of wheeze (–0.25), chest tightness (–0.27), and sleep disturbance (–0.25). For 12% of patients cough dominated patient preferences, regardless of all other symptoms. Age was inversely related to weight given by patients to breathlessness. CONCLUSIONS The prominence of cough among other asthma symptoms was unexpected. Daytime cough and breathlessness had greater impact for patients than wheeze or sleep disturbance. Age influenced symptom burden, with younger patients giving greater weight to breathlessness than older patients. Conjoint analysis appears to be a useful method for establishing the relative importance of common symptoms.
Speaker adaptation for audio-visual speech recognition

The restricted discharge orifice in a nozzle for an injection molding machine is normally held closed by a valve member in the nozzle bore which engages a valve seat in the bore contiguously adjacent the orifice. The valve member is biased toward the closed position by a helical compression spring in the nozzle bore. The spring is a metal strip of rectangular cross section whose narrow edges bound the steeply helical gap separating the spring turns. The valve is opened by the pressure of the molten plastic when used on a screw-type injection machine, or by engagement of the mold with an abutment projecting from the valve member outward of the nozzle orifice in the closed position of the valve, when the nozzle is used on a plunger-type molding machine.
Enhancing experience prototyping by the help of mixed-fidelity prototypes

In this research review I undertook the problem related to the usage of a new concept known as the Mixed- Fidelity Prototype which is a mixture of its predecessors Low- and High- Fidelity Prototypes in Experience Prototyping. Experience Prototyping is a good way to explore, communicate and interact with the designs we develop like experiencing cycling on the ice, although the mood, snow conditions, bicycle type and many other factors really matter and tend to change with time. Experience Prototyping in itself is a very large domain to be explored separately but this research contains the idea to improve the ways we can achieve these factors with a minimal variation. Prototyping has the involvement of both the users and the stake holders so it is really important that correct experiments and the prototypes should get the desired results. With the effective usage of mixed-fidelity prototype in Experience Prototyping a better understanding of the real system can be developed as it gives a feeling of both the Low- and High- Fidelity Prototypes. It can unable an HCI developer to properly identify the requirements either functional or non-functional as identified by the proposed user. This paper has a comparison study between the uses of different prototyping models in Experience prototyping for better understanding of the system under development in detail and reasons for preferring Mixed-Fidelity Prototypes over the others.
Extracting grid cell characteristics from place cell inputs using non-negative principal component analysis

Many recent models study the downstream projection from grid cells to place cells, while recent data have pointed out the importance of the feedback projection. We thus asked how grid cells are affected by the nature of the input from the place cells. We propose a single-layer neural network with feedforward weights connecting place-like input cells to grid cell outputs. Place-to-grid weights are learned via a generalized Hebbian rule. The architecture of this network highly resembles neural networks used to perform Principal Component Analysis (PCA). Both numerical results and analytic considerations indicate that if the components of the feedforward neural network are non-negative, the output converges to a hexagonal lattice. Without the non-negativity constraint, the output converges to a square lattice. Consistent with experiments, grid spacing ratio between the first two consecutive modules is −1.4. Our results express a possible linkage between place cell to grid cell interactions and PCA. DOI: http://dx.doi. org/10.7554/eLife.10094. 001
Performance evaluation of the HepB Typer-Entecavir kit for detection of entecavir resistance mutations in chronic hepatitis B

Background/Aims Molecular diagnostic methods have enabled the rapid diagnosis of drug-resistant mutations in hepatitis B virus (HBV) and have reduced both unnecessary therapeutic interventions and medical costs. In this study we evaluated the analytical and clinical performances of the HepB Typer-Entecavir kit (GeneMatrix, Korea) in detecting entecavir-resistance-associated mutations. Methods The HepB Typer-Entecavir kit was evaluated for its limit of detection, interference, cross-reactivity, and precision using HBV reference standards made by diluting high-titer viral stocks in HBV-negative human serum. The performance of the HepB Typer-Entecavir kit for detecting mutations related to entecavir resistance was compared with direct sequencing for 396 clinical samples from 108 patients. Results Using the reference standards, the detection limit of the HepB Typer-Entecavir kit was found to be as low as 500 copies/mL. No cross-reactivity was observed, and elevated levels of various interfering substances did not adversely affect its analytical performance. The precision test conducted by repetitive analysis of 2,400 replicates with reference standards at various concentrations showed 99.9% agreement (2398/2400). The overall concordance rate between the HepB Typer-Entecavir kit and direct sequencing assays in 396 clinical samples was 99.5%. Conclusions The HepB Typer-Entecavir kit showed high reliability and precision, and comparable sensitivity and specificity for detecting mutant virus populations in reference and clinical samples in comparison with direct sequencing. Therefore, this assay would be clinically useful in the diagnosis of entecavir-resistance-associated mutations in chronic hepatitis B.
Patterns of Synonymous Codon Usage in Drosophila melanogaster Genes With Sex-Biased Expression

The nonrandom use of synonymous codons (codon bias) is a well-established phenomenon in Drosophila. Recent reports suggest that levels of codon bias differ among genes that are differentially expressed between the sexes, with male-expressed genes showing less codon bias than female-expressed genes. To examine the relationship between sex-biased gene expression and level of codon bias on a genomic scale, we surveyed synonymous codon usage in 7276 D. melanogaster genes that were classified as male-, female-, or non-sex-biased in their expression in microarray experiments. We found that male-biased genes have significantly less codon bias than both female- and non-sex-biased genes. This pattern holds for both germline and somatically expressed genes. Furthermore, we find a significantly negative correlation between level of codon bias and degree of sex-biased expression for male-biased genes. In contrast, female-biased genes do not differ from non-sex-biased genes in their level of codon bias and show a significantly positive correlation between codon bias and degree of sex-biased expression. These observations cannot be explained by differences in chromosomal distribution, mutational processes, recombinational environment, gene length, or absolute expression level among genes of the different expression classes. We propose that the observed codon bias differences result from differences in selection at synonymous and/or linked nonsynonymous sites between genes with male- and female-biased expression.
Planes, trains and automobiles — autonomy for the modern robot

We are concerned with enabling truly large scale autonomous navigation in typical human environments. To this end we describe the acquisition and modeling of large urban spaces from data that reflects human sensory input. Over 181GB of image and inertial data are captured using head-mounted stereo cameras. This data is processed into a relative map covering 121 km of Southern England. We point out the numerous challenges we encounter, and highlight in particular the problem of undetected ego-motion, which occurs when the robot finds itself on-or-within a moving frame of reference. In contrast to global-frame representations, we find that the continuous relative representation naturally accommodates moving-reference-frames - without having to identify them first, and without inconsistency. Within a moving-reference-frame, and without drift-less global exteroceptive sensing, motion with respect to the global-frame is effectively unobservable. This underlying truth drives us towards relative topometric solutions like relative bundle adjustment (RBA), which has no problem representing distance and metric Euclidean structure, yet does not suffer inconsistency introduced by the attempt to solve in the global-frame.
Correlation between gene expression and GO semantic similarity

This research analyzes some aspects of the relationship between gene expression, gene function, and gene annotation. Many recent studies are implicitly based on the assumption that gene products that are biologically and functionally related would maintain this similarity both in their expression profiles as well as in their gene ontology (GO) annotation. We analyze how accurate this assumption proves to be using real publicly available data. We also aim to validate a measure of semantic similarity for GO annotation. We use the Pearson correlation coefficient and its absolute value as a measure of similarity between expression profiles of gene products. We explore a number of semantic similarity measures (Resnik, Jiang, and Lin) and compute the similarity between gene products annotated using the GO. Finally, we compute correlation coefficients to compare gene expression similarity against GO semantic similarity. Our results suggest that the Resnik similarity measure outperforms the others and seems better suited for use in gene ontology. We also deduce that there seems to be correlation between semantic similarity in the GO annotation and gene expression for the three GO ontologies. We show that this correlation is negligible up to a certain semantic similarity value; then, for higher similarity values, the relationship trend becomes almost linear. These results can be used to augment the knowledge provided by clustering algorithms and in the development of bioinformatic tools for finding and characterizing gene products.
Noninvasive ventilation for acute respiratory failure: a prospective randomised placebo-controlled trial

The aim of the present study was to clarify whether the known effects of noninvasive positive-pressure ventilation (NPPV) in patients with respiratory failure are real or due to placebo effects and whether early application of NPPV in the emergency department leads to rapid improvement of the patients condition and outcome. A prospective randomised placebo-controlled study was conducted in 20 patients with severe acute respiratory failure (ARF) secondary to an acute exacerbation of chronic obstructive pulmonary disease (COPD) or acute pulmonary oedema, not improving under conventional medical therapy and on the edge of intubation. Patients received either conventional medical therapy plus two-level NPPV (bi-level NPPV) or conventional medical therapy plus “placebo” NPPV. The main outcome measures involved the need for endotracheal intubation in the bi-level NPPV arm and in the placebo arm after crossing over to active NPPV. Morbidity, length of stay, mortality and the effect of the ventilatory mode on clinical, arterial-blood gas parameters, and the sternocleidomastoid muscles electromyogram (EMG) activity were also measured. The 10 patients in the active NPPV group rapidly improved and none needed intubation. Placebo NPPV resulted in no change in the clinical condition of patients that continued to worsen and the 10 patients were crossed over to active NPPV. Three patients were intubated. No differences in terms of morbidity, length of stay or mortality between the two groups were observed. Active NPPV (but not placebo NPPV) led to a rapid and significant improvement in the clinical parameters, pH and the carbon dioxide tension in arterial blood and to a decrease in respiratory frequency and sternocleidomastoid EMG activity. Early application of bi-level noninvasive positive-pressure ventilation in patients with severe acute respiratory failure, due to chronic obstructive pulmonary disease and acute pulmonary oedema, leads to a rapid improvement in clinical status and blood gases. Noninvasive positive-pressure ventilation had no placebo effect.
Reduced Differentiation Potential of Primary MyoD−/− Myogenic Cells Derived from Adult Skeletal Muscle

To gain insight into the regeneration deficit of MyoD−/− muscle, we investigated the growth and differentiation of cultured MyoD−/− myogenic cells. Primary MyoD−/− myogenic cells exhibited a stellate morphology distinct from the compact morphology of wild-type myoblasts, and expressed c-met, a receptor tyrosine kinase expressed in satellite cells. However, MyoD−/− myogenic cells did not express desmin, an intermediate filament protein typically expressed in cultured myoblasts in vitro and myogenic precursor cells in vivo. Northern analysis indicated that proliferating MyoD−/− myogenic cells expressed fourfold higher levels of Myf-5 and sixfold higher levels of PEA3, an ETS-domain transcription factor expressed in newly activated satellite cells. Under conditions that normally induce differentiation, MyoD−/− cells continued to proliferate and with delayed kinetics yielded reduced numbers of predominantly mononuclear myocytes. Northern analysis revealed delayed induction of myogenin, MRF4, and other differentiation-specific markers although p21 was upregulated normally. Expression of M-cadherin mRNA was severely decreased whereas expression of IGF-1 was markedly increased in MyoD−/− myogenic cells. Mixing of lacZ-labeled MyoD−/− cells and wild-type myoblasts revealed a strict autonomy in differentiation potential. Transfection of a MyoD-expression cassette restored cytomorphology and rescued the differentiation deficit. We interpret these data to suggest that MyoD−/− myogenic cells represent an intermediate stage between a quiescent satellite cell and a myogenic precursor cell.
Knee Laxity Variations in the Menstrual Cycle in Female Athletes Referred to the Orthopedic Clinic

Background Anterior cruciate ligament (ACL) rupture is the biggest concern for orthopedic surgeons who are involved in sports injuries, so most of ACL reconstruction surgeries are sports related. ACL injuries in female athletes are 2 - 8 times more common than male athletes in similar sport injuries. Objectives The aim of this study was to compare knee laxity changes in the menstrual cycle in female athletes referred to the orthopedic clinic of Imam Khomeini hospital in the north of Iran, Sari, 2013. Patients and Methods The present descriptive study was conducted on 40 female athletes that were referred to the orthopedic clinic. Hormone levels, such as estrogen and progesterone were assessed by one laboratory in 3 phases of the menstrual cycle. We used Lachman test and anterior drawer test for knee laxity rate. The descriptive statistics were calculated as indices of central distribution of bonds (x ± SD) and relative frequency distribution was used for qualitative variables. Results The results of the current study showed that there is no significant difference in ACL laxity in female athletes in three phases of menstrual cycle; namely menstruation time, ovulation time and mid-luteal phase. Conclusions Despite numerous studies and research in the field of knee laxity and effects of female hormones, many researchers do not agree about the effect of female hormones on knee laxity. The current study also reported no relationship between female hormones and knee laxity, while statistics show fundamental difference between male and female athletes.
Funnel control for speed & position control of electrical drives: A survey

In this survey we introduce a simple high-gain based adaptive controller — the funnel controller — which neither identifies nor estimates the system under control. The proportional funnel controller is applicable for all (nonlinear) systems with relative degree one or two, stable zero-dynamics (e.g. minimum-phase in the linear case) and known sign of the high-frequency gain; hence only structural knowledge is required for controller implementation. The control performance is inherently robust to parameter uncertainties or variations not affecting the system structure. Furthermore, the funnel controller is capable of reference tracking of time-varying command signals with prescribed transient accuracy: the control error is forced to evolve within a prescribed “funnel”. Its boundary can be fixed by e.g. a decreasing function of time giving an upper bound on the error transient behavior. Finally, we apply the funnel controller for speed and position control of an (unknown) electrical drive with friction and load disturbances. Measurement results are presented and compared with classical PI/PID control. funnel control, non-identifier (high-gain) based adaptive control, prescribed tracking, prescribed accuracy, robustness.
IEEE Transactions on Intelligent Transportation Systems

1  Abstract—This paper proposes a convolution neural network (CNN)-based method that learns traffic as images and predicts large-scale, network-wide traffic speed with high accuracy. Spatiotemporal traffic dynamics is converted to images describing the time and space relations of traffic flow via a two-dimensional time-space matrix. CNN is applied to the image following two consecutive steps: abstract traffic feature extraction and network-wide traffic speed prediction. The effectiveness of the proposed method is evaluated by taking two real-world transportation networks, the second ring road and northeast transportation network in Beijing, as examples, and comparing the method with four prevailing algorithms, namely, ordinary least squares, k-nearest neighbors, artificial neural network, and random forest. The results show that the proposed method outperforms the four algorithms by an average accuracy improvement of 27.96% within acceptable execution time. The CNN can train the model in reasonable time and thus are suitable for large-scale transportation networks.