Miracle-dz/UniFAR-FTUs huggingface dataset:
Multi-view learning with dependent views

Multi-view algorithms, such as co-training and co-EM, utilize unlabeled data when the available attributes can be split into independent and compatible subsets. Experiments have shown that multi-view learning is sometimes beneficial for problems for which the independence assumption is not satisfied. In practice, unfortunately, it is not possible to measure the dependency between two attribute sets; hence, there is no criterion which allows to decide whether multi-view learning is applicable. We conduct experiments with various text classification problems and investigate on the effectiveness of the co-trained SVM and the co-EM SVM under various conditions, including violations of the independence assumption. We identify the error correlation coefficient of the initial classifiers as an elaborate indicator of the expected benefit of multi-view learning.
Simple method for rapid diagnosis of catheter-associated infection by direct acridine orange staining of catheter tips

Direct acridine orange (AO) staining was used to detect bacteria adherent to intravascular catheters (IVC). Samples from 710 IVC tips were first cultured on blood agar plates by a semiquantitative technique and then independently colored with AO and screened dry at a magnification of x100 for 3 min. In the absence of fluorescence, they were considered negative. When fluorescence was present, they were further examined for the presence of microorganisms at x1,000 with immersion oil. Of 710 IVC tips, 37 (5.2%) were positive upon culture (greater than or equal to 15 colonies) and 673 were negative (640 were sterile and 33 [4.6%] had 1 to 14 colonies). The AO sensitivity was 84%, and the AO specificity was 99%. When restricted to the 212 long IVC, AO sensitivity rose to 94%. AO staining was positive in all cases of catheter-associated bacteremia. The negative predictive value of the preliminary screening at x100 was 99.5%. The direct examination of IVC tips stained by AO appears to be a simple and rapid method for diagnosing IVC-associated infections. In addition, AO staining is easier to perform than Gram staining.
Uncorrelated multiview discriminant locality preserving projection analysis for multiview facial expression recognition

Recently several multi-view learning-based methods have been proposed, and they are found to be more efficient in many real world applications. However, existing multi-view learning-based methods are not suitable for finding discriminative directions if the data is multi-modal. In such cases, Locality Preserving Projection (LPP) and/or Local Fisher Discriminant Analysis (LFDA) are found to be more appropriate to capture discriminative directions. Furthermore, existing methods show that imposing uncorrelated constraint onto the common space improves classification accuracy of the system. Hence inspired from the above findings, we propose an Un-correlated Multi-view Discriminant Locality Preserving Projection (UMvDLPP)-based approach. The proposed method searches a common uncorrelated discriminative space for multiple observable spaces. Moreover, the proposed method can also handle the multimodal characteristic, which is inherently embedded in multi-view facial expression recognition (FER) data. Hence, the proposed method is effectively more efficient for multi-view FER problem. Experimental results show that the proposed method outperforms state-of-the-art multi-view learning-based methods.
PSMA-Targeted Theranostic Nanocarrier for Prostate Cancer

Herein, we report the use of a theranostic nanocarrier (Folate-HBPE(CT20p)) to deliver a therapeutic peptide to prostate cancer tumors that express PSMA (folate hydrolase 1). The therapeutic peptide (CT20p) targets and inhibits the chaperonin-containing TCP-1 (CCT) protein-folding complex, is selectively cytotoxic to cancer cells, and is non-toxic to normal tissue. With the delivery of CT20p to prostate cancer cells via PSMA, a dual level of cancer specificity is achieved: (1) selective targeting to PSMA-expressing prostate tumors, and (2) specific cytotoxicity to cancer cells with minimal toxicity to normal cells. The PSMA-targeting theranostic nanocarrier can image PSMA-expressing cells and tumors when a near infrared dye is used as cargo. Meanwhile, it can be used to treat PSMA-expressing tumors when a therapeutic, such as the CT20p peptide, is encapsulated within the nanocarrier. Even when these PSMA-targeting nanocarriers are taken up by macrophages, minimal cell death is observed in these cells, in contrast with doxorubicin-based therapeutics that result in significant macrophage death. Incubation of PSMA-expressing prostate cancer cells with the Folate-HBPE(CT20p) nanocarriers induces considerable changes in cell morphology, reduction in the levels of integrin β1, and lower cell adhesion, eventually resulting in cell death. These results are relevant as integrin β1 plays a key role in prostate cancer invasion and metastatic potential. In addition, the use of the developed PSMA-targeting nanocarrier facilitates the selective in vivo delivery of CT20p to PSMA-positive tumor, inducing significant reduction in tumor size.
Employing Consumer Wearables to Detect Office Workers' Cognitive Load for Interruption Management

Office workers' productivity and well-being are reduced by interruptions, especially if they occur during an inconvenient moment. Interruptions in phases of high cognitive load are more disruptive than in phases of low cognitive load. Based on an explorative study, we suppose the presence of social codes that signal office workers' interruptibility. We propose a system that utilizes the cognitive load of an office worker to indicate situations suitable for interruptions. The cognitive load is inferred from office workers' physiological state measured by a consumer smartwatch. The system adapts an externally mounted smart device to indicate if the office worker is interruptible. To predict the cognitive load, we trained a classifier with ten office workers and achieved an accuracy between 66% and 86%. In order to validate the classifier's accurateness in an office setting, we performed a verification study with five office workers: We systematically triggered interruptions for each subject over an interval of half a day of office work. The classifier was able to infer the level of cognitive load for three office workers. This result supports our hypotheses that inferring cognitive load using a consumer smartwatch is a viable concept.
A hollow stainless steel microneedle array to deliver insulin to a diabetic rat

A novel fabrication process has been described for the development of a hollow stainless steel microneedle array using femto second laser micromachining. Using this method, a complicated microstructure can be fabricated in a single process step without using masks. The mechanical stability of the fabricated microneedle array was measured for axial and transverse loading. Skin histology was carried out to study the microneedle penetration into the rat skin. Fluid flow through the microneedle array was studied for different inlet pressures. The packaging of the microneedle array, to protect the microneedle bore blockage from dust and other atmospheric contaminations, was also considered. Finally, the microneedle array was tested and studied in vivo for insulin delivery to a diabetic rat. The results obtained were compared with the standard subcutaneous delivery with the same dose rate and were found to be in good agreement.
Development and Utilisation of Fibre Optic-based Monitoring Systems for Underground Coal Mines

The continuous economic growth and depleting shallow reserves have increased the number of deeper mining operations worldwide which has made safety and productivity more challenging due to the higher stresses, heat and increased gas contents. Any major improvements in safety and productivity require a reliable and real-time monitoring system that provides more comprehensive information about various processes. The current monitoring systems suffer from lack of reliability, accuracy and high capital and operating costs. Recent advancements in fibre-optic based sensing technology have introduced unique solutions for various underground coal mine applications such as health and safety, geotechnical, ventilation, borehole, mine environment and condition monitoring. This paper presents recent research, development and utilisation of this technology by a group of researchers at the University of Queensland (UQ) and CRCMining in Australia and Shandong Academy of Science in China. A fibre-optic cable normally consists of a number of optical fibres. An optical fibre mainly consists of three components: the core, the cladding and the coating. The typical structure of an optical fibre is presented in Figure 1. Light propagates mainly along the core of the fibre that is generally made of glass or plastic. The cladding layer is also made of glass or plastic but with a smaller index of refraction compared to that of the core. The role of the cladding is to keep the light within the core and prevent any loss of light from the core into the surrounding. The cladding also increases the strength of the fibre and protects it from the environmental effects. Extra protection of the fibre is provided by the coating that is a layer of plastic on the cladding.
A review on machine learning principles for multi-view biological data integration

Driven by high-throughput sequencing techniques, modern genomic and clinical studies are in a strong need of integrative machine learning models for better use of vast volumes of heterogeneous information in the deep understanding of biological systems and the development of predictive models. How data from multiple sources (called multi-view data) are incorporated in a learning system is a key step for successful analysis. In this article, we provide a comprehensive review on omics and clinical data integration techniques, from a machine learning perspective, for various analyses such as prediction, clustering, dimension reduction and association. We shall show that Bayesian models are able to use prior information and model measurements with various distributions; tree-based methods can either build a tree with all features or collectively make a final decision based on trees learned from each view; kernel methods fuse the similarity matrices learned from individual views together for a final similarity matrix or learning model; network-based fusion methods are capable of inferring direct and indirect associations in a heterogeneous network; matrix factorization models have potential to learn interactions among features from different views; and a range of deep neural networks can be integrated in multi-modal learning for capturing the complex mechanism of biological systems.
A Simulation Approach to Evaluate Supply Policies of a Pig Slurry Treatment Plant by Multiple Farms

This paper describes the use of a dynamical simulation model to evaluate various management policies in a two-stage production systems. Such a simulation-based evaluation is applied to the situation of GrandIlet (Reunion Island) where 51 pig farms must supply a collective treatment plant (CTP) with pig slurry. Based on actual data and stakeholders’ preferences, three policies are tested: a planned policy with fixed delivery period and delivery size and two reactive policies with time-varying order points and replenishment levels: one based on farm stocks, the other based on the CTP stock. The reactive policy focused on farm stocks is judged most adapted to meet the management goals (no stock overflow, robustness) even with random disturbances.
Bing-SF-IDF+: a hybrid semantics-driven news recommender

Content-based news recommendation is traditionally performed using the cosine similarity and the TF-IDF weighting scheme for terms occurring in news messages and user profiles. Semantics-driven variants such as SF-IDF additionally take into account term meaning by exploiting synsets from semantic lexicons. However, they ignore the various semantic relationships between synsets, providing only for a limited understanding of news semantics. Moreover, semantics-based weighting techniques are not able to handle -- often crucial -- named entities, which are often not present in semantic lexicons. Hence, we extend SF-IDF by also considering the synset semantic relationships, and by employing named entity similarities using Bing page counts. Our proposed method, Bing-SF-IDF+, outperforms TF-IDF and SF-IDF in terms of F1-scores and kappa statistics based on a news data set.
Variation in the association of Der p 1 and Der f 1 with asthma and rhinitis in 9‐11‐year‐old schoolchildren: The French six cities study

Allergic asthma and rhinitis largely occur due to atopic sensitization to different allergens. Several studies have firmly established that allergic sensitization to indoor dust mites, as assessed by specific immunoglobulin E (IgE) or skin prick tests to specific allergens, is significantly related to respiratory allergic symptoms [1-4]. Among the house dust mites, Dermatophagoides pteronyssinus (Der p 1) and Dermatophagoides farinae (Der f 1) are the most potent mites that can cause an exacerbation in the case of allergic rhinitis and asthma [5]. Moreover, dust allergens are often found as one of the most important risk factors for asthma during childhood [6]. Although the clinical symptoms of chronic asthma and rhinitis can be traced back to silent sensitization of mite allergens at the early years of life, the pathological effect in the lung function becomes more pronounced at a later stage of the paediatric population [7]. This article is protected by copyright. All rights reserved.
STUDY ON COMBUSTION CHARACTERISTIC OF MICRO PULVERIZED COAL

Micro pulverized coal (0 20μm) combustion technology is a kind of new technology in pulverized coal combustion technologies. By comparison, micro pulverized coal combustion technology has many advantages than common pulverized coal combustion technology, such as better combustion stability, higher efficiency, lower NOx pollution, better synthetic efficiency, etc. At the case of simple equal weight of samples, same condition of experiences and same 20℃/min heating rate, this paper apply STA 409C thermobalance made in Germany analyzing respectively samples from Heshan and Jincheng whose average sizes are all different. The experimental results show that the micro pulverized coal has better combustion characteristics than common pulverized coal.
Multi-Agent-Based Generation of Explanations for Retrieval Results Within a Case-Based Support Framework for Architectural Design

: In this paper, we describe the general structure and evaluation of a multi-agent based system module that was conceptualized to explain, and therefore, enrich the search results of the retrieval process within a distributed case-based framework for support of early conceptual design phase in architecture. This explanation module is implemented as an essential part of the framework and uses case-based agents, explanation ontology, and explanation patterns as its underlying foundational components. The module’s main goal is to provide the user with additional information about the search results to make the framework’s behavior during the retrieval stage more transparent and traceable. System’s justiﬁcation for displaying of results plays an important role as well, and is also included in the explanations. We evaluated the explanation generation process with a ground-truth set of explanations and a case-based validation process to ensure the suitability of the generated explanation expressions for displaying in user interfaces connected to the framework. The results of the evaluation conﬁrmed our expectation and showed the general validity of the explanations.
Contiguity Between Ablation Lesions and Strict Catheter Stability Settings Assessed by VISITAGTM Module Improve Clinical Outcomes of Paroxysmal Atrial Fibrillation Ablation　- Results From the VISITALY Study.

BACKGROUND Our aim was to evaluate the clinical outcome of paroxysmal atrial fibrillation (AF) ablation with contact force technology, using an automated lesion tagging system (VISITAGTM module) with strict criteria of catheter stability.Methods and Results:We enrolled 200 consecutive patients who underwent pulmonary vein isolation (PVI) in 11 centers and were followed up for 12 months. The stability setting was within 3 mm for ≥10 s and for ≥15 s in 47% and 53% of patients, respectively. A mean of 67.2±21.9 VISITAGs was acquired. Freedom from atrial tachyarrhythmias at follow-up was 77.5% (155/200), and the contiguity between lesions was associated with a higher chronic success rate (96% vs. 77.1%; log-rank P=0.036). Radiofrequency (RF), fluoroscopy times, and recurrence rates at the 12-month follow-up were significantly lower than in a comparison group of 80 patients without VISITAGTM module (42.7±14.5 vs. 50.9±23.6 min; P=0.032; 11.6±7.8 vs. 18.4±12.8 min; P=0.003 and 22.5% vs. 41.2%; P=0.02). Two major complications (1 cardiac tamponade and 1 minor stroke) were observed only in the control group. CONCLUSIONS Paroxysmal AF ablation with contact force technology and strict criteria of stability using the VISITAG module was a safe procedure, associated with an improvement in efficiency and a reduction of atrial tachyarrhythmia recurrence at the 12-month follow-up compared with manual annotation. Contiguity between lesions seemed to enhance effectiveness outcomes.
Texture adaptive steganography via Convolutional Neural Networks

For the investigation of the steganography, most of the current algorithms focus on how to describe the noise of an image. This paper proposes a new paradigm for steganography to automatically evaluating the modification priority of each pixel in image by using Convolutional Neural Networks (CNN). An image is decomposed into several sub-images which center pixel is modified, steganalysis method is used to judge which sub-image is secure, this suggests the center pixel suitable to embed message or not and obtain an appropriate priority. Corresponding stenographic cost assigned to each pixel on the foundation of priority. Experiments show that the proposed method achieves the state-of-the art performance on resisting advanced steganalysis.
Modeling and Qualitative Evaluation of a Management Canvas for Big Data Applications

A reference model for big data management is proposed, together with a methodology for business enterprises to bootstrap big data projects. Similar to the business model canvas for marketing management, the big data management (BDM) canvas is a template for developing new (or mapping existing) big data applications, strategies and projects. It subdivides this task into meaningful fields of action. The BDM canvas provides a visual chart that can be used in workshops iteratively to develop strategies for generating value from data. It can also be used for project planning and project progress reporting. The canvas instantiates a big data reference meta-model, the BDM cube, which provides its meta-structure. In addition to developing and theorizing the proposed data management model, two case studies on pilot applications in companies in Switzerland and Austria provide a qualitative evaluation of our approach. Using the insights from expert feedback, we provide an outlook for further research.
Intravascular Imaging of Lipid Core Plaque by Near-Infrared Spectroscopy

Intracoronary near-infrared spectroscopy (NIRS) is a novel catheter-based technique that allows determination of the chemical composition of the coronary artery wall. This is accomplished by measuring the proportion of near-infrared light diffusely reflected by the arterial wall after scattering and absorption have occurred. Histology and clinical studies have validated that NIRS can detect with high accuracy the presence of coronary lipid core plaques, which form the substrate for most acute coronary syndromes and complicate stenting procedures. Coronary NIRS is currently being evaluated as a tool to: (Clarke, Figg, & Maguire, 2006) optimize the outcomes of percutaneous coronary interventions (PCI), (Ross, 1999) identify coronary lesions at risk for causing events and optimize the medical management of such patients, and (Kagan, Livsic, Sternby, & Vihert, 1968) allow evaluation of novel anti-atherosclerotic treatments. DOI: 10.4018/978-1-61350-095-8.ch014
Effectiveness of protected areas for vertebrates based on taxonomic and phylogenetic diversity

Establishing protected areas is the primary goal and tool for preventing irreversible biodiversity loss. However, the effectiveness of protected areas that target specific species has been questioned for some time because targeting key species for conservation may impair the integral regional pool of species diversity and phylogenetic and functional diversity are seldom considered. We assessed the efficacy of protected areas in China for the conservation of phylogenetic diversity based on the ranges and phylogenies of 2279 terrestrial vertebrates. Phylogenetic and taxonomic diversity were strongly and positively correlated, and only 12.1–43.8% of priority conservation areas are currently protected. However, the patterns and coverage of phylogenetic diversity were affected when weighted by species richness. These results indicated that in China, protected areas targeting high species richness protected phylogenetic diversity well overall but failed to do so in some regions with more unique or threatened communities (e.g., coastal areas of eastern China, where severely threatened avian communities were less protected). Our results suggest that the current distribution of protected areas could be improved, although most protected areas protect both taxonomic and phylogenetic diversity.
Structure of the Large Magellanic Cloud from the Near Infrared magnitudes of Red Clump stars

The structural parameters, like the inclination, i and the position angle of the line of nodes (PA_lon) of the disk of the Large Magellanic Cloud (LMC) are estimated using the JH photometric data of red clump stars from the Infrared Survey Facility - Magellanic Cloud Point Source Catalog (IRSF-MCPSC). The observed LMC region is divided into several sub-regions and stars in each region are cross identified with the optically identified red clump stars to obtain the near infrared magnitudes. The peak values of H magnitude and (J-H) colour of the observed red clump distribution are obtained by fitting a profile to the distributions and also by taking the average value of magnitude and colour of the red clump stars in the bin with largest number. Then the dereddened peak H0 magnitude of the red clump stars in each sub-region is obtained. The RA, Dec and relative distance from the center of each sub-region are converted into x, y & z Cartesian coordinates. A weighted least square plane fitting method is applied to this x,y,z data to estimate the structural parameters of the LMC disk. A reddening map based on (J-H) colour of the RC stars is presented. When the peaks of the red clump distribution were identified by averaging, an inclination of 25.7 +/- 1.6 and PA_lon = 141.5 +/- 4.5 were obtained. We estimate a distance modulus of 18.47 +/- 0.1 mag to the LMC. Extra-planar features which are in front as well as behind the fitted plane are identified which match with the optically identified extra-planar features. The bar of the LMC is found to be part of the disk within 500 pc. The estimates of the structural parameters are found to be independent of the photometric bands used for the analysis. We find that the inner disk, within 3.0, is less inclined and has larger value of PA_lon when compared to the outer disk.