Miracle-dz/UniFAR-FTUs huggingface dataset:
Advanced laser in-situ joining for continuous co-consolidation of carbon fiber-reinforced thermoplastic laminates

Advanced laser in-situ joining (CONTIjoin) is a newly developed process for continuous co-consolidation of multidirectional carbon fiber-reinforced thermoplastic laminates onto a substrate material. In contrast to traditional lay-up techniques, like automated fiber placement (AFP) or automated tape laying (ATL), the CONTIjoin process is capable of continuous in-situ co-consolidation of laminates with up to six plies instead of single-layer unidirectional tapes. In the process, a carbon dioxide (CO 2 ) laser in combination with highly dynamic beam deflection is used to heat up the joining partners in the mating area, while a pyrometer feeds temperature information into a control circuit to maintain a high set temperature accuracy. Without further autoclave post-processing, over 90 % of the mechanical performance of a static heat press co-consolidation was shown in interlaminar shear strength (ILSS) tests. The results are part of the Clean Sky 2 campaign for joining two thermoplastic half-shells of the full-scale multifunctional fuselage demonstrator (MFFD).
Integration of on‐chip peristaltic pumps and injection valves with microchip electrophoresis and electrochemical detection

A microfluidic approach that integrates peristaltic pumping from an on‐chip reservoir with injection valves, microchip electrophoresis and electrochemical detection is described. Fabrication and operation of both the peristaltic pumps and injection valves were optimized to ensure efficient pumping and discrete injections. The final device uses the peristaltic pumps to continuously direct sample from a reservoir containing a mixture of analytes to injection valves that are coupled with microchip electrophoresis and amperometric detection. The separation and direct detection of dopamine and norepinephrine were possible with this approach and the utility of the device was demonstrated by monitoring the stimulated release of these neurotransmitters from a layer of cells introduced into the microchip. It is also shown that this pumping/reservoir approach can be expanded to multiple reservoirs and pumps, where one reservoir can be addressed individually or multiple reservoirs sampled simultaneously.
A geometric approach to joint inversion with applications to contaminant source zone characterization

This paper presents a new joint inversion approach to shape-based inverse problems. Given two sets of data from distinct physical models, the main objective is to obtain a unified characterization of inclusions within the spatial domain of the physical properties to be reconstructed. Although our proposed method generally applies to many types of inverse problems, the main motivation here is to characterize subsurface contaminant source zones by processing down-gradient hydrological data and cross-gradient electrical resistance tomography observations. Inspired by Newton's method for multi-objective optimization, we present an iterative inversion scheme in which descent steps are chosen to simultaneously reduce both data-model misfit terms. Such an approach, however, requires solving a non-smooth convex problem at every iteration, which is computationally expensive for a pixel-based inversion over the whole domain. Instead, we employ a parametric level set technique that substantially reduces the number of underlying parameters, making the inversion computationally tractable. The performance of the technique is examined and discussed through the reconstruction of source zone architectures that are representative of dense non-aqueous phase liquid (DNAPL) contaminant release in a statistically homogenous sandy aquifer. In these examples, the geometric configuration of the DNAPL mass is considered along with additional information about its spatial variability within the contaminated zone, such as the identification of low and high saturation regions. Comparison of the reconstructions with the true DNAPL architectures highlights the superior performance of the model-based technique and joint inversion scheme.
Associations of

It has been demonstrated that physical activity has a small but positive effect on cognition in old age, which suggests that it may be possible to alter the trajectory of age-related cognitive decline. However, our understanding of which aspects of physical activity that are important for modifying cognition remains incomplete. Adopting an exploratory approach in a sample of 115 healthy older adults (65 – 75 years), the present cross-sectional study used structural equation modelling to investigate the dissociable associations of physical activity (moderate-to-vigorous activity, derived from 7-day accelerometry) and cardiorespiratory fitness (VO 2 max, derived from maximal treadmill ergometer test) with multiple latent cognitive abilities (working memory, episodic memory, spatial and verbal reasoning). The results showed a significant positive association between fitness and working memory, when physical activity was statistically controlled for, and a positive association of similar point magnitude between physical activity and episodic memory, when fitness was statistically controlled for, although the latter association did not reach statistical significance. The results add to the foundation for a more careful investigation of the dissociable associations of moderate-to-vigorous physical activity and fitness with cognition in old age, and encourages future research to test the hypothesis that cardiorespiratory fitness benefits working memory via general cerebrovascular effects on grey matter volume, whilst moderate-to-vigorous physical activity benefits episodic memory via effects on neuroplastic processes.
Regularized Multi-Concept MIL for weakly-supervised facial behavior categorization

In this work, we address the problem of estimating high-level semantic labels for videos of recorded people by means of analysing their facial expressions. This problem, to which we refer as facial behavior categorization, is a weakly-supervised learning problem where we do not have access to frame-by-frame facial gesture annotations but only weak-labels at the video level are available. Therefore, the goal is to learn a set of discriminative expressions appearing during the training videos and how they determine these labels. Facial behavior categorization can be posed as a Multi-Instance-Learning (MIL) problem and we propose a novel MIL method called Regularized Multi-Concept MIL to solve it. In contrast to previous approaches applied in facial behavior analysis, RMC-MIL follows a Multi-Concept assumption which allows different facial expressions (concepts) to contribute differently to the video-label. Moreover, to handle with the high-dimensional nature of facial-descriptors, RMC-MIL uses a discriminative approach to model the concepts and structured sparsity regularization to discard non-informative features. RMC-MIL is posed as a convex-constrained optimization problem where all the parameters are jointly learned using the Projected-Quasi-Newton method. In our experiments, we use two public data-sets to show the advantages of the Regularized MultiConcept approach and its improvement compared to existing MIL methods. RMC-MIL outperforms state-of-the-art results in the UNBC data-set for pain detection.
Universal HbA1c Measurement in Early Pregnancy to Detect Type 2 Diabetes Reduces Ethnic Disparities in Antenatal Diabetes Screening: A Population-Based Observational Study

In response to the type 2 diabetes epidemic, measuring HbA1c with the first-antenatal blood screen was recently recommended in NZ. This would enable prompt treatment of women with unrecognised type 2 diabetes, who may otherwise go undetected until the gestational diabetes (GDM) screen. We compare inter-ethnic antenatal screening practices to examine whether the HbA1c test would be accessed by ethnicities most at risk of diabetes, and we determined the prevalence of unrecognised type 2 diabetes and prediabetes in our pregnant population. This is an observational study of pregnancies in Christchurch NZ during 2008–2010. Utilising electronic databases, we matched maternal characteristics to first-antenatal bloods, HbA1c, and GDM screens (glucose challenge tests and oral glucose tolerance tests). Overall uptake of the first-antenatal bloods versus GDM screening was 83.1% and 53.8% respectively in 11,580 pregnancies. GDM screening was lowest in Māori 39.3%, incidence proportion ratio (IPR) 0.77 (0.71, 0.84) compared with Europeans. By including HbA1c with the first-antenatal bloods, the number screened for diabetes increases by 28.5% in Europeans, 40.0% in Māori, 28.1% in Pacific People, and 26.7% in ‘Others’ (majority of Asian descent). The combined prevalence of unrecognised type 2 diabetes and prediabetes by NZ criteria, HbA1c ≥5.9% (41mmol/mol), was 2.1% in Europeans, Māori 4.7% IPR 2.59 (1.71, 3.93), Pacific People 9.5% IPR 4.76 (3.10, 7.30), and ‘Others’ 6.2% IPR 2.99 (2.19, 4.07). Applying these prevalence data to 2013 NZ national births data, routine antenatal HbA1c testing could have identified type 2 diabetes in 0.44% and prediabetes in 3.96% of women. Routine HbA1c measurement in early pregnancy is an ideal screening opportunity, particularly benefitting vulnerable groups, reducing ethnic disparities in antenatal diabetes screening. This approach is likely to have world-wide relevance and applicability. Further research is underway to establish whether, as for type 2 diabetes, prompt treatment of prediabetes improves pregnancy and neonatal outcomes.
A system for real-time detection and tracking of vehicles from a single car-mounted camera

A novel system for detection and tracking of vehicles from a single car-mounted camera is presented. The core of the system are high-performance vision algorithms: the WaldBoost detector [1] and the TLD tracker [2] that are scheduled so that a real-time performance is achieved. The vehicle monitoring system is evaluated on a new dataset collected on Italian motorways which is provided with approximate ground truth (GT0) obtained from laser scans. For a wide range of distances, the recall and precision of detection for cars are excellent. Statistics for trucks are also reported. The dataset with the ground truth is made public.
Glucuronidation of Anticancer Prodrug PR-104A: Species Differences, Identification of Human UDP-Glucuronosyltransferases, and Implications for Therapy

PR-104, the phosphate ester of a dinitrobenzamide mustard [PR-104A; 2-((2-bromoethyl)-2-{[(2-hydroxyethyl) amino] carbonyl}-4,6-dinitroanilino)ethyl methanesulfonate], is currently in clinical trial as a hypoxia- and aldo-keto reductase 1C3 (AKR1C3)-activated prodrug for cancer therapy. Here, we investigate species (human, dog, rat, mouse) differences in metabolism to the corresponding O-glucuronide, PR-104G, and identify the human UDP-glucuronosyltransferase (UGT) isoforms responsible. After intravenous PR-104, plasma area under the concentration-time curve ratios (PR-104G/PR-104A) decreased in the order of dog (2.3) > human (1.3) > mouse (0.03) > rat (0.005). The kinetics of uridine 5′-diphosphoglucuronic acid-dependent glucuronidation by liver microsomes in vitro fitted the single-enzyme Michaelis-Menten equation with similar Km (∼150 μM) but differing Vmax (472, 88, 37, and 14 nmol/h/mg for dog, human, rat, and mouse, respectively), suggesting that facile glucuronidation is responsible for the anomalously rapid clearance of PR-104A in dogs. In vitro-in vivo extrapolation of PR-104A glucuronidation kinetics is consistent with this also being a major clearance pathway in humans. Recombinant UGT screening identified UGT2B7 as the only commercially available human isoform able to conjugate PR-104A, and UGT2B7 protein concentrations were highly correlated (r = 0.93) with PR-104A glucuronidation by liver microsomes from 24 individuals. The active hydroxylamine metabolite of PR-104A, PR-104H, was also glucuronidated by UGT2B7, although with slightly lower specificity and much lower rates. UGT2B7 mRNA expression was highly variable in human tumor databases. Glucuronidation of PR-104A greatly suppressed nitroreduction by AKR1C3 and NADPH-supplemented anoxic human liver S9 (9000g postmitochondrial supernatant). In conclusion, PR-104A is glucuronidated by UGT2B7 with high specificity and seems to make a major contribution to clearance of PR-104A in humans, but it also has the potential to confer resistance in some human tumors.
A Comparison of Knowledge-based Algorithms for Graded Word Sense Assignment

Standard word sense disambiguation (WSD) data sets annotate each word instance in context with exactly one sense of a predefined inventory, and WSD systems are traditionally evaluated with regard to how good they are at picking this sense. Recently, the notion of graded word sense assignment (GWSA) has gained attention as a more natural view of the contextual specification of word meaning; multiple senses may apply simultaneously to one instance of a word, and they may be applicable to different degrees. In this paper, we apply three different WSD algorithms to the task of GWSA. The three models belong to the class of knowledge-based models in the WSD terminology; they are unsupervised in the sense that they do not depend on annotated training material. We evaluate the models on two recently published GWSA data sets. We find positive correlations with the human judgments for all models, and develop a metric based on the notion of accuracy that highlights differences in the behaviors of the models.
Text classiﬁcation with semantically enriched word embeddings

The recent breakthroughs in deep neural architectures across multiple machine learning ﬁelds have led to the widespread use of deep neural models. These learners are often applied as black-box models that ignore or insuﬃciently utilize a wealth of pre-existing semantic information. In this study, we focus on the text classiﬁcation task, investigating methods for augmenting the input to deep neural networks with semantic information. We extract semantics for the words in the preprocessed text from the WordNet semantic graph, in the form of weighted concept terms that form a semantic frequency vector. Concepts are selected via a variety of semantic disambiguation techniques, including a basic, a part-of-speech-based and a semantic embedding projection method. Additionally, we consider a weight propagation mechanism that exploits semantic relationships in the concept graph and conveys a spreading activation component. We enrich word2vec embed-dings with the resulting semantic vector through concatenation or replacement and apply the semantically augmented word embeddings on the classiﬁcation task via a deep neural network. Experimental results over established datasets demonstrate that our approach of semantic augmentation in the input space boosts classiﬁcation performance signiﬁcantly, with concatenation oﬀering the best performance. We also note additional interesting ﬁndings produced by our approach regarding the behaviour of TF-IDF normalization on semantic vectors, along with the radical dimensionality reduction potential with negligible performance loss.
Robot-assisted partial nephrectomy: evolution and recent advances

Purpose of review Robot-assisted partial nephrectomy (RAPN) is emerging as a viable complement to traditional laparoscopic and open partial nephrectomy. As a relatively new technique, the techniques and technologies employed during RAPN continue to evolve. In the present article, we provide an overview of the evolution of robot-assisted renal surgery, and highlight the recent advances that have helped to bring RAPN to the fore. Recent findings The learning curve for RAPN appears to be slight, and technical proficiency may be quickly achieved, even for those with limited laparoscopic experience. Recent advances include improvements in ergonomics of the robotic system itself, as well as the introduction of sliding-clip renorrhaphy, early unclamping techniques, and off-clamp techniques. Early-to-intermediate outcomes are very promising, demonstrating short warm ischemic times, and a low rate of complication and recurrence. Disadvantages to the approach include substantial cost, as well as increased reliance upon the assistant to perform critical maneuvers. Summary Robot-assisted partial nephrectomy appears to be a safe and efficacious technique for the surgical management of localized renal malignancy. Recent developments have focused upon reducing ischemic insult, as well as decreasing reliance upon the assistant.
Self-optimization of capacity and coverage in LTE networks using a fuzzy reinforcement learning approach

This paper introduces a solution to enable self-optimization of coverage and capacity in LTE networks through base stations' downtilt angle adjustment. The proposed method is based on fuzzy reinforcement learning techniques and operates in a fully distributed and autonomous fashion without any need for a priori information or human interventions. The solution is shown to be capable of handling extremely noisy feedback information from mobile users as well as being responsive to the changes in the environment including self-healing properties. The simulation results confirm the convergence of the solution to the global optimal settings and that the proposed scheme provides up to 20% performance improvement when compared with an existing fuzzy logic based reinforcement learning approach.
ATP Changes the Fluorescence Lifetime of Cyan Fluorescent Protein via an Interaction with His148

Recently, we described that ATP induces changes in YFP/CFP fluorescence intensities of Fluorescence Resonance Energy Transfer (FRET) sensors based on CFP-YFP. To get insight into this phenomenon, we employed fluorescence lifetime spectroscopy to analyze the influence of ATP on these fluorescent proteins in more detail. Using different donor and acceptor pairs we found that ATP only affected the CFP-YFP based versions. Subsequent analysis of purified monomers of the used proteins showed that ATP has a direct effect on the fluorescence lifetime properties of CFP. Since the fluorescence lifetime analysis of CFP is rather complicated by the existence of different lifetimes, we tested a variant of CFP, i.e. Cerulean, as a monomer and in our FRET constructs. Surprisingly, this CFP variant shows no ATP concentration dependent changes in the fluorescence lifetime. The most important difference between CFP and Cerulean is a histidine residue at position 148. Indeed, changing this histidine in CFP into an aspartic acid results in identical fluorescence properties as observed for the Cerulean fluorescent based FRET sensor. We therefore conclude that the changes in fluorescence lifetime of CFP are affected specifically by possible electrostatic interactions of the negative charge of ATP with the positively charged histidine at position 148. Clearly, further physicochemical characterization is needed to explain the sensitivity of CFP fluorescence properties to changes in environmental (i.e. ATP concentrations) conditions.
A Study on the Role of non-Hyperlink Text on Web Navigation

Cognitive models of web navigation have been used for evaluating websites and predicting user navigation behavior. Currently they predict the correct hyperlink by using information from the hyperlink text alone and ignore all other textual information on a webpage. The validity of this assumption is examined by investigating the role of non-hyperlink text on user navigation behavior. In the first experiment, we created two versions of a website by removing the non-hyperlink text from it. We found that there was no significant effect of non-hyperlink text on the user navigation behavior. Participants were equally accurate, selected the same set of pages to visit and spent the same amount of time on that common set with or without non-hyperlink text. This result validates the assumptions of those models of user-navigation behavior that consider information from the hyperlink text only. However, in a followup experiment, we included high-relevance and low-relevance pictures on the website, and repeated the experiment with and without non-hyperlink text. We found that participants were more accurate in the presence of non-hyperlink text than without it. This result suggests that the presence of pictures might prime the users to pay attention to non-hyperlink text, which increases the task accuracy.
Molecular Detection and Characterization of Fusarium sporotrichioides based on ITS2 rDNA Polymorphism

The genus Fusarium contains a number of soil-borne species with worldwide distribution. The presented PCR assays are highly selective and sensitive in detecting the Fusarium genus. In order to identify the eighteen Fusarium isolates obtained at the molecular level. PCR analysis using primer specific for the conserved ITS DNA region of Fusarium genus was conducted. The data indicated that all of the eighteen isolates showed a clear band corresponding to the expected molecular size of the ITS region (431bp). These results confirmed that all the tested samples belong to the genus Fusarium. Also, when all eighteen isolates of Fusarium species were analyzed by PCR for fumonisin producing ability using FUM1 gene-based primers, the expected DNA fragment of 183 bp was amplified only in Fusarium verticillioides (3 isolates), Fusarium avenaceum (3 isolates), Fusarium semitectum (1 isolate) and Fusarium culmorum (2 isolates) showed a positive result with FUM1 gene set of primers. No bands were seen in other isolates of Fusarium spp. and the standard (Fusarium graminearum). In case of zearalenone, the PKS4 gene of F. graminearum has been reported to be essential for the production of zearalenone. The result indicated that the expected DNA fragment of 280 bp was amplified only in Fusarium verticillioides (3 isolates), Fusarium avenaceum (3 isolates) and Fusarium culmorum (2 isolates) and Fusarium graminearum. Microsatellite-primed PCR resembles the well-known RAPD technique but is advantageous because of the ability to generate more complex banding patterns and a high degree of reproducibility. The discriminating powers of the three MP-primers [(CTG)5, (M13) and (T3B)] used in this study were nearly the same. Cluster analyses were performed on the genomic fingerprints generated by each of the primers tested. Three dendrograms were generated with the UPGMA method. The patterns resulting from the T3B and (CTG)5 test were more distinct and T3B was the most successful primer because it always led to high polymorphic banding patterns that were suitable for interspecies comparisons. Our results indicated that there was no association between clustering in the MP-PCR dendrogram and the geographic origin and morphological identification of the tested isolates. Ekram A. M. Al-Sanae, Afaf I. Shehata, Ali H. Bahkali, , Mohammed Abdo Yahya and Amal A. Al
SATIN: a toolkit for informal ink-based applications

Software support for making effective pen-based applications is currently rudimentary. To facilitate the creation of such applications, we have developed SATIN, a Java-based toolkit designed to support the creation of applications that leverage the informal nature of pens. This support includes a scenegraph for manipulating and rendering objects; support for zooming and rotating objects, switching between multiple views of an object, integration of pen input with interpreters, libraries for manipulating ink strokes, widgets optimized for pens, and compatibility with Java’s Swing toolkit. SATIN includes a generalized architecture for handling pen input, consisting of recognizers, interpreters, and multi-interpreters. In this paper, we describe the functionality and architecture of SATIN, using two applications built with SATIN as examples.