Miracle-dz/UniFAR-FTUs huggingface dataset:
HST image restoration developments at the ST‐ECF

When spherical aberration was found to be degrading the performance of the Hubble Space Telescope (HST), great interest in image restoration methods arose in the astronomical community. The Richardson‐Lucy (RL) method became the preferred tool for restoring such data which typically has Poisson noise characteristics and a low signal‐to‐noise ratio. Subsequently, corrective optics were inserted into the telescope which is now operating close to the original specifications. However, generalized RL methods and some new techniques based on projections onto convex sets have proved useful both for the present HST data, which are often insufficiently sampled, and also for many other classes of astronomical images. The ST‐ECF staff have worked extensively in this and related areas, and some of these developments and their application to real data are described.
A new wide band printed antenna

This paper presents the characteristics of a new wide band printed microstrip antenna. This antenna is designed to operate in the C-band, with an impedance bandwidth of about 35% around 5GHz for a standing wave ratio (SWR) less than 2. The antenna consists of probe fed segmented patch. A narrow slit is made in the patch around the feed region. Design parameters and results are presented.
A classification model of ERP system data quality

Purpose – In literature, there is not agreement on the relevant data quality dimensions in an enterprise resource planning (ERP) system context. The purpose of this paper is to provide some clarification of this topic, by answering two important questions: What are the most relevant dimensions for assessing ERP data quality? What are the causal relationships between these data quality dimensions? Design/methodology/approach – Based on a discussion of existing literature on data quality, a classification model of ERP system data quality is proposed and the relationships between the defined categories of data quality dimensions are defined. The validity of the classification model and the relationships between categories of data quality dimensions are investigated in three case studies.Findings – The three case studies confirm that the classification model captures the most important aspects of describing ERP data quality and that the defined causalities between categories of data quality dimensions correspo.
Exploring Success Factors of Social Infrastructure Projects in Malaysia

In the context of construction management, Social Infrastructure Projects (SIPs) have long been overlooked. However, SIPs are one of the main criteria for enhancing economic productivity. This paper analyses the results of a survey aiming to develop a framework for SIP success factors to enhance the likelihood of success in the provision of SIPs in Malaysia. The principal component analysis reduces a set of 41 project success factors to six dimensions based on the idea of the project life cycle, i.e., the preconstruction factor, the construction factor and post-construction factor, and three internal factors: the organizational factor, the information management factor, and the change management factor. Understanding these success factors could be crucial in managing SIPs, since it will allow project stakeholders to take precautionary steps to identify foreseeable problems and areas for improvement. This will increase the success rate of the project and could even help avoid problems completely.
Chromatic aberration reduction through optical feature modeling

This paper presents a method of digitally removing or correcting Chromatic Aberration (CA) of lens, which generally occurs in an edge region of image. Based on the information of the lens's and sensor's features in camera, it determines CA level and the dominant chrominance of CA and efficiently removes extreme CA such as purple fringe and blooming artifacts, as well as a general CA to be generated at an edge in an image captured by a camera. Firstly, this method includes a CA region sensing part analyzing a luminance signal of an input image and sensing a region having CA. Secondly, the CA level sensing part calculates the weight, which indicates a degree of CA, based on a difference between gradients of color components of the input image. Thirdly, for removing the extreme CA such as purple fringe and blooming artifact which caused by the feature of lens and sensor, it uses 1-D Gaussian filters having different sigma values to get the weight. The sigma value indicates the feature of lens and sensor. And, for removing the general CA, it includes the adaptive filter, based on luminance signal. Finally, by using these weights, final filter will be produced adaptively with the level of CA and lens's and sensor's features. Experimental results show the effectiveness of this proposed method.
On Polynomials Defined by Acyclic Conjunctive Queries and Weighted Counting Problems

This paper is a study of weighted counting problems associated to acyclic conjunctive queries ($\ACQ$) and the polynomials they define. We prove that summing the weights of solutions of quantifier-free $\ACQ$ queries can be done in polynomial time. We also show that minimalistic extensions of the problem (introducing one quantified variable, considering disjunction or conjunction of two $\ACQ$ instances) lead to intractable problems. However, we introduce a new parameter for quantified queries that permits to isolate large island of tractability. We show that, up to a standard assumption from parameterized complexity, this parameter fully characterizes tractable subclasses for counting weighted solutions of $\ACQ$ queries.
Lossy-to-lossless progressive coding of depth-maps

A progressive coding method is proposed for depth-map images, where the bitstream is encoded so that one can generate many lossy versions of the original, encompassing a wide range, from very low resolution up to lossless reconstruction. The partitions into regions of the lossy versions are assumed to be nested, so that a higher resolution image is obtained by splitting some regions of a lower resolution image. The encoder transmits to the decoder information about which regions to split, the extra contour to be added for obtaining the shapes of the more refined regions, and the extra depth values needed inside each new region. The efficient encoding of the anchor points in the progressive scenario, relative to the contour points already encoded, and the depth information recovery, are the main contributions of this paper. The progressive bitstream produced by the proposed method scales well over the whole range of rates, from low rates to lossless, reaching a performance close to that of the non-progressive methods.
Silexan, an orally administered Lavandula oil preparation, is effective in the treatment of ‘subsyndromal’ anxiety disorder: a randomized, double-blind, placebo controlled trial

This study was performed to investigate the anxiolytic efficacy of silexan, a new oral lavender oil capsule preparation, in comparison to placebo in primary care. In 27 general and psychiatric practices 221 adults suffering from anxiety disorder not otherwise specified (Diagnostic and Statistical Manual of Mental disorders–IV 300.00 or International Statistical Classification of Diseases and Related Health Problems, Tenth revision F41.9) were randomized to 80 mg/day of a defined, orally administered preparation from Lavandula species or placebo for 10 weeks with visits every 2 weeks. A Hamilton Anxiety Scale (HAMA) total score ≥18 and a total score >5 for the Pittsburgh Sleep Quality Index (PSQI) were required. The primary outcome measures were HAMA and PSQI total score decrease between baseline and week 10. Secondary efficacy measures included the Clinical Global Impressions scale, the Zung Self-rating Anxiety Scale, and the SF–36 Health Survey Questionnaire. Patients treated with silexan showed a total score decrease by 16.0±8.3 points (mean±SD, 59.3%) for the HAMA and by 5.5±4.4 points (44.7%) for the PSQI compared to 9.5±9.1 (35.4%) and 3.8±4.1 points (30.9%) in the placebo group (P<0.01 one-sided, intention to treat). Silexan was superior to placebo regarding the percentage of responders (76.9 vs. 49.1%, P<0.001) and remitters (60.6 vs. 42.6%, P=0.009). Lavandula oil preparation had a significant beneficial influence on quality and duration of sleep and improved general mental and physical health without causing any unwanted sedative or other drug specific effects. Lavandula oil preparation silexan is both efficacious and safe for the relief of anxiety disorder not otherwise specified. It has a clinically meaningful anxiolytic effect and alleviates anxiety related disturbed sleep.
Comparison of IEEE802.1Q and IEEE802.1AVB in multi switch environment in embedded system

Currently, Advanced Driver Assistance Systems (ADAS) require high bandwidth network. Ethernet supports 100Mbit / s bandwidth, which is worth using in future automotive networks. However, unlike CAN, which is widely used in automotive networks, Ethernet does not support the priority of the frame, so it can not guarantee Quality of Service (QoS). IEEE802.1Q (802.1Q) and IEEE802.1AVB (AVB) of the IEEE802 Ethernet standard have a priority mechanism, but there is a difference. The existing papers analyze QoS of 802.1Q and AVB in simulation environment. In this paper, we compare the QoS of 802.1Q and AVB in a network environment implemented with embedded system and multiple switches. So AVB and 802.1Q analyze the QoS according to the priority mechanism.
Hybrid Deep Network and Polar Transformation Features for Static Hand Gesture Recognition in Depth Data

Static hand gesture recognition is an interesting and challenging problem in computer vision. It is considered a significant component of Human Computer Interaction and it has attracted many research efforts from the computer vision community in recent decades for its high potential applications, such as game interaction and sign language recognition. With the recent advent of the cost-effective Kinect, depth cameras have received a great deal of attention from researchers. It promoted interest within the vision and robotics community for its broad applications. In this paper, we propose the effective hand segmentation from the full depth image that is important step before extracting the features to represent for hand gesture. We also represent the novel hand descriptor explicitly encodes the shape and appearance information from depth maps that are significant characteristics for static hand gestures. We propose hand descriptor based on Polar Transformation coordinate is called Histogram of Polar Transformation (HPT) in order to capture both shape and appearance. Beside a robust hand descriptor, a robust classification model also plays a very important role in the hand recognition model. In order to have a high performance in recognition rate, we propose hybrid model for classification based on Sparse Auto-encoder and Deep Neural Network. We demonstrate large improvements over the state-of-the-art methods on two challenging benchmark datasets are NTU Hand Digits and ASL Finger Spelling and achieve the overall accuracy as 97.7% and 84.58%, respectively. Our experiments show that the proposed method significantly outperforms state-of-the-art techniques.
Rotigaptide (ZP123) Reverts Established Atrial Conduction Velocity Slowing

Rotigaptide (ZP123) increases gap junction intercellular communication (GJIC) and prevents stress-induced cardiac conduction velocity (CV) slowing. However, the effect of rotigaptide on established cardiac conduction slowing and the duration of effect on rotigaptide during washout is unknown. Metabolic stress (induced by superfusion with nonoxygenated glucose-free Tyrodes buffer) was associated with a 30% decrease in atrial CV in vehicle-treated rat atria. Rotigaptide treatment initiated after a period of 30 minutes of metabolic stress produced a rapid and significant increase in CV compared to vehicle-treated time controls. During washout of rotigaptide for 30 min (while subjected to metabolic stress), there was a minor decrease in atrial CV; however, this was not significantly different from atrial CV in a rotigaptide-treated time control group. Rotigaptide treatment rapidly normalizes established conduction slowing in atria subjected to metabolic stress. However, the cessation of effect was considerably slower than the onset of action.
Future perspectives in Orbitrap™-high-resolution mass spectrometry in food analysis: a review

A literature search from 2007 to 2014 was conducted to identify publications where principally LC-Orbitrap™-high-resolution mass spectrometry (HRMS) has been employed in food analysis. Of a total of 212 relevant references, only 22 papers were from 2007–10, but in subsequent years there has been a steady growth in publications with 38–55 relevant papers being published each year from 2011 to 2014. In the food safety area, over 50% of the published papers were equally divided between pesticides, veterinary drug residues and natural toxins (including mycotoxins) focused primarily on multi-analyte target analysis. LC-Orbitrap-HRMS was also found to be increasingly important for the analysis of bioactive substances, principally phenolic compounds in foods. A number of studies reported for the first time the identification of new fungal metabolites, predominantly various conjugated forms of known mycotoxins. Novel process contaminants were also identified by LC-Orbitrap-HRMS, as were various substances used for food adulteration and bioactive substances in herbal products and dietary supplements. Untargeted analysis is seen as a major future trend where HRMS plays a significant role. Retrospective analysis of scanned high-resolution mass spectra in conjunction with relevant databases can provide new insights. Metabolomics is also being increasingly used where foods are being profiled through fingerprinting using HRMS. All evidence points towards future growth in the number of applications of HRMS in food safety and quality, as the power of this technique gains wider recognition. Graphical Abstract
The societal burden of pain in Germany: Health-related quality-of-life, health status and direct medical costs

Abstract Objectives: The purpose of this paper is to estimate the impact of the severity and frequency of pain on health-related quality-of-life (HRQoL), self-reported health status, and direct medical costs in Germany. Methods: Data are from the internet-based 2010 National Health and Wellness Survey (NHWS). Estimates of the impact of pain experience are generated by a series of regression models. In the case of HRQoL the physical and mental summary scores from the SF-12, together with SF-6D utilities, are evaluated within an ordinary least squares framework. Health status is assessed through an ordered logit model. Direct medical costs are estimated through a semi-logarithmic healthcare cost function. Socioeconomic characteristics, health risk behaviors, and the Charlson Comorbidity Index (CCI) are introduced as control variables in all regressions. Results: An estimated 23.96% of the adult German population (16.39 million) reported experiencing pain in the last 30 days. Of these 13.16% reported severe pain. The experience of frequent severe and moderate pain has a significant deficit impact on HRQoL. For those experiencing severe daily pain, the deficit in the SF-12 physical component score (PCS) is −17.930 (95% CI: −18.720 to −17.140), the SF-12 mental component score (MCS) is −8.787 (05% CI: −9.857 to −7.716), and SF-6D absolute utilities −0.201 (95% CI: −0.214 to −0.188); with self-reported health status the deficit impact of severe daily pain is also substantial (OR = 29.000; 95% CI: 23.000–36.580). In the case of direct medical costs severe daily pain increases healthcare provider costs by 101.6% and total direct costs by 123.9%. Limitations: The NHWS is an internet survey. The principal limitation is that as a self-report there is no separate validation of pain severity or chronicity. Conclusions: The experience of pain has a substantial negative impact on HRQoL, health status, and resource utilization in Germany. If pain is considered as a disease in its own right, the experience of chronic pain presents policy-makers with a major challenge.
Adoção de Realidade Aumentada no Ensino de Resistência dos Materiais

Este trabalho tem como objetivo analisar a adocao de Realidade Aumentada - RA no ensino de Engenharia, a partir da perspectiva de estudantes da disciplina Resistencia dos Materiais ofertada pela Universidade X, tendo como elemento norteador o Modelo de Aceitacao de Tecnologia - TAM. A pesquisa contou com a participacao de 50 discentes que, inicialmente, realizaram um experimento seguindo um roteiro para testes de recursos de RA, associados ao conteudo da disciplina, e, em seguida, responderam a um questionario fundamentado no TAM. Os resultados indicam que os recursos tiveram uma boa aceitacao e que a adocao de RA contribui para o ensino de Resistencia dos Materiais, ajudando na apresentacao e compreensao do conteudo.
Evidence for Functional Conservation, Sufficiency, and Proteolytic Processing of the CLAVATA3 CLE Domain1[W][OA]

Arabidopsis (Arabidopsis thaliana) CLAVATA3 (CLV3) is hypothesized to act as a ligand for the CLV1 receptor kinase in the regulation of stem cell specification at shoot and flower meristems. CLV3 is a secreted protein, with an amino-terminal signal sequence and a conserved C-terminal domain of 15 amino acids, termed the CLE (CLV3/ESR-related) domain, based on its similarity to a largely unstudied protein family broadly present in land plants. We have tested the function of 13 Arabidopsis CLEs in vivo and found a significant variability in the ability of CLEs to replace CLV3, ranging from complete to no complementation. The best rescuing CLE depends on CLV1 for function, while other CLEs act independently of CLV1. Domain-swap experiments indicate that differences in function can be traced to the CLE domain within these proteins. Indeed, when the CLE domain of CLV3 is placed downstream of an unrelated signal sequence, it is capable of fully replacing CLV3 function. Finally, we have detected proteolytic activity in extracts from cauliflower (Brassica oleracea) that process both CLV3 and CLE1 at their C termini. For CLV3, processing appears to occur at the absolutely conserved arginine-70 found at the beginning of the CLE domain. We propose that CLV3 and other CLEs are C-terminally processed to generate an active CLE peptide.
Clustering via support vector machine boosting with simulated annealing

SVMs are shown to be effective at clustering when used with metaheuristics to recover label information in a bootstrap learning process. An automated tuning solution for Support Vector Machine (SVM) classification and clustering methods is described. This is shown for two complemetary situations: (1) by implementing a simulated annealing with perturbation tuning procedure on the relabeler-SVM boosted clustering method (single-pass), where kernel and algorithmic parameters are already optimized both by brute force computational search and by genetic algorithm evolutionary search; and (2) by implementing a multi-pass, random restart, SVM clustering optimization analysis (with fixed kernel and algorithmic parameters). Informatics-based SVM kernels, introduced previously, are used. Tuning is done by using the SVM performance on training data to define a fitness function. Tuning metaheuristics offer an automated way to obtain a powerful SVM classifier, or clustering process, for a given dataset. The SVM discussion is interwoven with data analysis involving channel current data, with specific application to the signal processing associated with the nanopore transduction detector. 54 Stephen Winters-Hilt
Short term wind power forecasting using Hilbert-Huang Transform and artificial neural network

Capacity and output power forecasting have great significance in seamless integration of renewable energy to the grid. However, the uncertainty of wind power and intermittence of wind energy are the main factors which affect forecasting precision. The wind power output data can be treated as a signal stream which has characteristics for possible wind capacity forecasting. Hilbert-Huang Transforms (HHT) and Hilbert spectral analysis have been applied extensively to analysis nonlinear and non-stationary stochastic signal. The time series of wind power output has been transformed into certain signals with different frequencies. Each signal is taken as input data joining with wind speed data to establish Artificial Neural Network (ANN) forecasting model. The models are combined together to obtain the final results on potential wind power output. This paper proposes HHT-ANN model for wind power forecasting. A case study of a wind farm in Texas, U.S shows that the MRE of proposed method is lower than the traditional ANN approach.
Hydraulic architecture of sugarcane in relation to patterns of water use during plant development

Hydraulic conductance was measured on leaf and stem segments excised from sugarcane plants at different stages of development. Maximum transpiration rates and leaf water potential (ΨL) associated with maximum transpiration were also measured in intact plants as a function of plant size. Leaf specific hydraulic conductivity (Lsc) and transpiration on a unit leaf area basis (E) were maximal in plants with approximately 0.2 m2 leaf area and decreased with increasing plant size. These changes in Fand Lsc were nearly parallel, which prevented φL in larger plants from decreasing to levels associated with substantial loss in xylem conductivity caused by embolism formation. Coordination of changes in E and leaf hydraulic properties was not mediated by declining leaf water status, since φL increased with plant size. Hydraulic constrictions were present at nodes and in the node-leaf sheath-leaf blade pathway. This pattern of constrictions is in accord with the idea of plant segmentation into regions differing in water transport efficiency and would tend to confine embolisms to the relatively expendable leaves at terminal positions in the pathway, thereby preserving water transport through the stem.
Ionic Selectivity , Saturation , and Block in Sodium Channels

A B S TR ACT Ionic fluxes in Na channels of myelinated axons show ionic competition, block, and deviations from simple flux independence. These phenomena are particularly evident when external Na + ions are replaced by other permeant or impermeant ions. The observed currents require new flux equations not based on the concepts of free diffusion. A specific permeability model for the Na channel is developed from Eyring rate theory applied to a chain of saturable binding sites. There are four energy barriers in the pore and only one ion is allowed inside at a time. Deviations from independence arise from saturation. The model shows that ionic permeability ratios measured from zero-current potentials can differ from those measured from relative current amplitudes or conductances. The model can be fitted to experiments with various external sodium substitutes by varying only two parameters: For each ion the height of the major energy barrier (the selectivity filter) determines the biionic zero-current potential and the depth of the energy well (binding site) just external to that barrier then determines the current amplitudes. Voltage clamp measurements with myelinated nerve fibers are given showing numerous examples of deviations from independence in ionic fluxes. Strong blocks of ionic currents by guanidinium compounds and T1 + ions are fitted by binding within the channel with apparent dissociation constants in the range 50-122 mM. A small block with high Na + concentrations can be fitted by Na + ion binding with a dissociation constant of 368 mM. The barrier model is given a molecular interpretation that includes stepwise dehydration of the permeating ion as it interacts with an ionized carboxylie acid.