Miracle-dz/UniFAR-FTUs huggingface dataset:
Transfer Learning with Ensemble of Multiple Feature Representations

Supervised learning algorithms are to discover the hidden patterns of the statistics, assuming that the training data and the test data are from the same distribution. There are two challenges in the traditional supervised machine learning. One is that the test data distribution always differs largely from the training data distribution in the real world, while another is that there is usually very few labeled data to train a machine learning model. In such cases, transfer learning, which emphasizes the transfer of the previous knowledge from different but related domains and tasks, is recommended to deal with these problems. Traditional transfer learning methods care more about the data itself rather than the task. In fact, there is no one universal feature representation can perfectly benefit the model training work. But different feature representations can discover some independent latent knowledge from the original data. In this paper, we propose an instance-based transfer learning method, which is a weighted ensemble transfer learning framework with multiple feature representations. In our work, mutual information is applied as the smart weighting schema to measure the weight of each feature representation. Extensive experiments have been conducted on three facial expression recognition data sets: JAFFE, KDEF and FERG-DB. The experimental results demonstrate that our approach achieves better performance than the traditional transfer learning method and the non-transfer learning method.
RECENT CHANGES IN INFECTIOUS DISEASES IN EUROPEAN WILDLIFE

Abstract: Many infectious diseases originating from, or carried by, wildlife affect wildlife conservation and biodiversity, livestock health, or human health. We provide an update on changes in the epidemiology of 25 selected infectious, wildlife-related diseases in Europe (from 2010–16) that had an impact, or may have a future impact, on the health of wildlife, livestock, and humans. These pathogens were selected based on their: 1) identification in recent Europe-wide projects as important surveillance targets, 2) inclusion in European Union legislation as pathogens requiring obligatory surveillance, 3) presence in recent literature on wildlife-related diseases in Europe since 2010, 4) inclusion in key pathogen lists released by the Office International des Epizooties, 5) identification in conference presentations and informal discussions on a group email list by a European network of wildlife disease scientists from the European Wildlife Disease Association, or 6) identification as pathogens with changes in their epidemiology during 2010–16. The wildlife pathogens or diseases included in this review are: avian influenza virus, seal influenza virus, lagoviruses, rabies virus, bat lyssaviruses, filoviruses, canine distemper virus, morbilliviruses in aquatic mammals, bluetongue virus, West Nile virus, hantaviruses, Schmallenberg virus, Crimean-Congo hemorrhagic fever virus, African swine fever virus, amphibian ranavirus, hepatitis E virus, bovine tuberculosis (Mycobacterium bovis), tularemia (Francisella tularensis), brucellosis (Brucella spp.), salmonellosis (Salmonella spp.), Coxiella burnetii, chytridiomycosis, Echinococcus multilocularis, Leishmania infantum, and chronic wasting disease. Further work is needed to identify all of the key drivers of disease change and emergence, as they appear to be influencing the incidence and spread of these pathogens in Europe. We present a summary of these recent changes during 2010–16 to discuss possible commonalities and drivers of disease change and to identify directions for future work on wildlife-related diseases in Europe. Many of the pathogens are entering Europe from other continents while others are expanding their ranges inside and beyond Europe. Surveillance for these wildlife-related diseases at a continental scale is therefore important for planet-wide assessment, awareness of, and preparedness for the risks they may pose to wildlife, domestic animal, and human health.
Smart Greenhouse Farming based on IOT

The fundamental idea is to increase the growth of different varieties of crops with good quality in a closed environment usually a Greenhouse. The proposed system can monitor the changes in factors like temperature, humidity, soil moisture by integrating the sensor elements to Raspberry pi and alerts the user through mobile application. Sensor values inserted on Raspberry pi MySQL database can be used to analyze agricultural data. The authenticated mobile application developed can be used to monitor the parameters, get latest agricultural updates of schemes and news, market crop rates, weather information etc. Government Market crop prices provided will prevent farmer from being exploited by middlemen's greediness.
The Relationship Between Response Consistency in Picture Naming and Storage Impairment in People With Semantic Variant Primary Progressive Aphasia

Objective: The progressive loss of stored knowledge about word meanings in semantic variant primary progressive aphasia (svPPA) has been attributed to an amodal “storage” deficit of the semantic system. Performance consistency has been proposed to be a key characteristic of storage deficits but has not been examined in close detail and larger participant cohorts. Method: We assessed whether 10 people with svPPA showed consistency in picture naming across 3 closely consecutive sessions. We examined item-by-item consistency of naming accuracy and specific error types, while controlling for the effects of word-related variables such as word frequency, familiarity, and age of acquisition. Results: Participants were very consistent in their accurate and inaccurate responses over and above any effects of the word-related variables. Analyses of error types that compared consistency of semantic errors, correct responses, and other error types (e.g., phonologically related errors, unrelated errors) revealed lower consistency. Conclusions: Our findings support the assumption that semantic features constituting semantic representations of objects are progressively lost in people with svPPA and are therefore consistently unavailable during naming. Variability in the production of error types occurs when distinctive features of an object are lost, resulting in the selection of semantically or visually similar items or in the failure to select an item and a response omission. The assessment of performance consistency sheds light on the underlying impairment of people with semantic deficits (semantic storage vs. access deficit). This can support the choice of an appropriate treatment technique to maintain or reteach semantic information.
A CHARACTERIZATION OF THE EDGE OF CRITICALITY IN BINARY ECHO STATE NETWORKS

Echo State Newtworks (ESNs) are simplified recurrent neural network models composed of a reservoir and a linear, trainable readout layer. The reservoir is tunable by some hyper-parameters that control the network behaviour. ESNs are known to be effective in solving tasks when configured on a region in (hyper-)parameter space called Edge of Criticality (EoC), where the system is maximally sensitive to perturbations hence affecting its behaviour. In this paper, we propose binary ESNs, which are architecturally equivalent to standard ESNs but consider binary activation functions and binary recurrent weights. For these networks, we derive a closed-form expression for the EoC in the autonomous case and perform simulations in order to assess their behavior in the case of noisy neurons and in the presence of a signal. We propose a theoretical explanation for the fact that the variance of the input plays a major role in characterizing the EoC.
Model Predictive Control of a Multilevel CHB STATCOM in Wind Farm Application Using Diophantine Equations

The finite control set model predictive control (FCS-MPC) for power electronic converters provides high dynamic performance, based on the limited number of inputs and accurate model of the converter. By applying this algorithm to multilevel converters such as a cascaded-H-bridge-based static var compensator (CHB STATCOM), the dynamic performance is degraded, because the optimized input is achieved by searching among a large set of switching combinations and redundancies. This paper proposes an FCS-MPC algorithm, which benefits high dynamic performance for the CHB STATCOM, despite the large set of inputs. The proposed FCS-MPC replaces the time-consuming optimization algorithm by solving Diophantine equations over the large set of switching combinations. The desired switching combination and all its redundancies are determined in a minimum execution time. The proposed FCS-MPC performance is validated by applying to two configurations: 1) a 15-level CHB STATCOM with energy storage capability for a short-term active power smoothing and reactive power compensation of a 10 MW fixed speed wind farm at medium voltage; and 2) an experimental seven-level CHB STATCOM at low voltage.
An Improved Face Recognition Algorithm Based on Sparse Representation

This paper considers a variation of Sparse Representation-based Classification algorithm. Accuracy and time of evaluation of face recognition are two key performance indicators. This work compares performance of modified Sparse Representation-based Classification algorithm against original Sparse Representation-based Classification algorithm. Yale Face Database B is used to carry MATLAB simulations and results show that modified Sparse Representation-based Classification algorithm outperforms in terms of time. Moreover, the authors study and compare these algorithms when there is only a few training samples per subject is available.
Efficacy and Safety of Antibiotic Therapy in Early Cutaneous Lyme Borreliosis: A Network Meta-analysis

Importance Controversies about the choice of antibiotic agent and treatment modality exist in the management of erythema migrans in early cutaneous Lyme borreliosis (LB). Objective To conduct a network meta-analysis (NMA) of all randomized clinical trials on various antibiotic agents and treatment modalities in early cutaneous LB. Data Sources Electronic searches in MEDLINE, Embase, and the Cochrane Central Register of Controlled Trials were conducted from inception until July 2017. The reference lists of the included studies were hand searched, authors were contacted, and ongoing trials were searched at ClinicalTrials.gov. Study Selection One reviewer screened the titles and abstracts of the 9975 reports identified by the electronic searches. Full-text copies of 161 potentially relevant articles were obtained, and 2 reviewers independently assessed those articles for inclusion. Adults with a physician-confirmed early localized skin infection who were treated with antibiotics of any dose or duration were included. Data Extraction and Synthesis Two reviewers independently extracted data on study, patient, and intervention characteristics. Network meta-analyses on treatment effects and adverse outcomes were calculated with a frequentist approach using the R package netmeta. The Grading of Recommendations Assessment, Development and Evaluation guidance for NMA was used to assess the certainty of evidence. Main Outcomes and Measures Treatment effects for response to treatment (resolution of symptoms) and treatment-related adverse events. Results Overall, 19 studies (2532 patients) were included. The mean patient age ranged between 37 and 56 years, and the percentage of female patients ranged from 36% to 60%. The antibiotics investigated were doxycycline, cefuroxime axetil, ceftriaxone, amoxicillin, azithromycin, penicillin V, and minocycline. Pooled effect sizes from NMAs did not suggest any significant differences in treatment response by antibiotic agent (eg, amoxicillin vs doxycycline odds ratio, 1.26; 95% CI, 0.41-3.87), dose, or duration (eg, doxycycline, 200 mg/d for 3 weeks, vs doxycycline, 200 mg/d for 2 weeks, odds ratio, 1.28; 95% CI, 0.49-3.34). Treatment failures were rare at both 2 months (4%; 95% CI, 2%-5%) and 12 months (2%, 95% CI, 1%-3%) after treatment initiation. There were also no differences in the effect sizes among antibiotic agents and treatment modalities for treatment-related adverse outcomes, which were generally mild to moderate. Certainty of evidence was categorized as low and very low mostly because of imprecision, indirectness, and study limitations (high risk of bias) of the included studies. Conclusions and Relevance This NMA suggests that neither the antibiotic agent nor treatment modality contributed to comparative effectiveness or drug-related adverse outcomes. This finding is relevant for physicians treating patients with LB and for patient decision making.
A Novel approach for Extracting and Combining relevant Web Content

Researching about a particular topic on the World Wide Web has become difficult because of the wide range of websites, repetitive content on these websites and irrelevant data like ads on each websites. Websites have become integral part of any system aiming to collect data about a topic because they contain a lot of it. As for researchers, they require all the information that they can gather for giving accurate and unique conclusions. In the current scenario of search engines, there is a lack of surety of getting all required information quickly and correctly. During many search results lesser important webpages show up on top of some good ones. It is manual task to visit different pages, find the actual content in between noisy and irrelevant data like advertisements and gather required data from different webpages. It is time consuming and inefficient in a world where data has become most important source of any system. This paper proposes a novel approach to create a system that aims to make the job easy for anyone willing to get relevant information about a particular topic with just a few clicks. Our proposed system gathers information from various webpages combines the data and displays it in a categorized manner.
Comparative Analysis of Hybrid Clustering Algorithm on Different Dataset

Clustering is a data mining technique, in which data is grouped based on similarity and dissimilarity. Clustering is usually used to identify hidden pattern in multidimensional complex data and, these hidden pattern provide bases for making decisions. The objective of this research to find the best clustering algorithm. K-Mean is a famous clustering algorithm, which is simple and easy to implement, but the drawback of K-Mean is that, it does not work with higher dimensional data, for aiding with this drawback K-Mean is fused with other clustering algorithms such as PSO (Particle Swarm optimization) and PCA (Principle Component Analysis) for better results and cluster identifications. In this paper authors used hybrid clustering approach (K-Mean, PSO-K-Mean and PCA-K-Mean) to improve the clustering result based on parameter (Purity, Rand index and Computation Time) on different data sets taken from UCI Repository.
A Post-Quantum One Time Signature Using Bloom Filter

Today's commonly used digital signatures will not be secure if a quantum computer exists. One time signatures (OTS) base security on the one way property of hash functions and will stay secure against an adversary with access to a quantum computer. These schemes however suffer from large public and private keys, as well as large signature size. We propose an OTS that uses Bloom filters to enhance the efficiency without sacrificing security, and show the required sizes of public/private keys, as well as the signature size will all reduce for the same security level.
Higher Dispersion Measures of Conduction and Repolarization in Type 1 Compared to Non-type 1 Brugada Syndrome Patients: An Electrocardiographic Study From a Single Center

Background: Brugada syndrome (BrS) is a cardiac ion channelopathy that predisposes affected individuals to sudden cardiac death (SCD). Type 1 BrS is thought to take a more malignant clinical course than non-type 1 BrS. We hypothesized that the degrees of abnormal repolarization and conduction are greater in type 1 subjects and these differences can be detected by electrocardiography (ECG). Methods: Electrocardiographic data from spontaneous type 1 and non-type 1 BrS patients were analyzed. ECG parameters were measured from leads V1 to V3. Values were expressed as median [lower quartile-upper quartile] and compared using Kruskal-Wallis ANOVA. Results: Compared to non-type 1 BrS patients (n = 29), patients with spontaneous type 1 patterns (n = 22) showed similar (P > 0.05) heart rate (73 [64–77] vs. 68 [62–80] bpm), QRS duration (136 [124–161] vs. 127 [117–144] ms), uncorrected QT (418 [393–443] vs. 402 [386–424] ms) and corrected QT intervals (457 [414–474] vs. 430 [417–457] ms), JTpeak intervals (174 [144–183] vs. 174 [150–188] ms), Tpeak− Tend intervals (101 [93–120] vs. 99 [90–105] ms), Tpeak− Tend/QT ratios (0.25 [0.23–0.27] vs. 0.24 [0.22–0.27]), Tpeak− Tend/QRS (0.77 [0.62–0.87] vs. 0.77 [0.69–0.86]), Tpeak− Tend/(QRS × QT) (0.00074 [0.00034–0.00096] vs. 0.00073 [0.00048–0.00012] ms−1), index of Cardiac Electrophysiological Balance (iCEB, QT/QRS, marker of wavelength: 3.14 [2.56–3.35] vs. 3.21 [2.85–3.46]) and corrected iCEB (QTc/QRS: 3.25 [2.91–3.73] vs. 3.49 [2.99–3.78]). Higher QRS dispersion was seen in type 1 subjects (QRSd: 34 [24–66] vs. 24 [12–34] ms) but QT dispersion (QTd: 48 [39–71] vs. 43 [22–94] ms), QTc dispersion (QTcd: 52 [41–79] vs. 46 [23–104] ms), JTpeak dispersion (44 [23–62] vs. 45 [30–62] ms), Tpeak− Tend dispersion (28 [15–34] vs. 29 [22–53] ms) or Tpeak− Tend/QT dispersion (0.06 [0.03–0.08] vs. 0.08 [0.04–0.12]) did not differ between the two groups. Type 1 subjects showed higher (QRSd × Tpeak− Tend)/QRS (25 [19–44] vs. 19 [9–30] ms) but similar iCEB dispersion (0.83 [0.49–1.14] vs. 0.61 [0.34–0.92]) and iCEBc dispersion (0.93 [0.51–1.15] vs. 0.65 [0.39–0.96]). Conclusion: Higher levels of dispersion in conduction and repolarization are found in type 1 than non-type 1 BrS patients, potentially explaining the higher incidence of ventricular arrhythmias in the former group.
A Study on Neonatal Intake of Oleanolic Acid and Metformin in Rats (Rattus norvegicus) with Metabolic Dysfunction: Implications on Lipid Metabolism and Glucose Transport

Metabolic syndrome, a cluster of different disorders which include diabetes, obesity and cardiovascular diseases, is a global epidemic that is growing at an alarming rate. The origins of disease can be traced back to early developmental stages of life. This has increased mortalities and continues to reduce life expectancies of individuals across the globe. The aim of this study was to investigate the sub-acute and long term effects of neonatal oral administration of oleanolic acid and metformin on lipids (free fatty acids, FFAs) and genes associated with lipid metabolism and glucose transport using a neonatal rat experimental model. In the first study, seven days old pups were randomly grouped into control—distilled water (DW); oleanolic acid (60 mg/kg), metformin (500 mg/kg), high fructose diet (20% w/v, HF), oleanolic acid (OA) + high fructose diet (OA + HF), and Metformin + high fructose diet (MET + HF) groups. The pups were treated for 7 days, and then terminated on postnatal day (PD) 14. In the second study, rat pups were initially treated similarly to study 1 and weaned onto normal rat chow and plain drinking water on PD 21 till they reached adulthood (PD112). Tissue and blood samples were collected for further analyses. Measurement of the levels of free fatty acids (FFAs) was done using gas chromatography-mass spectrometry. Quantitative polymerase chain reaction (qPCR) was used to analyze the gene expression of glut-4, glut-5, fas, acc-1, nrf-1 and cpt-1 in the skeletal muscle. The results showed that HF accelerated accumulation of saturated FFAs within skeletal muscles. The HF fed neonatal rats had increased stearic acid, which was associated with decreased glucose, suppressed expression of glut-4, glut-5, nrf-1 and cpt-1 genes, and increased expression of acc-1 (p < 0.01) and fas. OA + HF and MET + HF treated groups had increased mono- and polyunsaturated FFAs; oleic, and octadecadienoic acids than the HF group. These unsaturated FFAs were associated with increased glut-4, glut-5 and nrf-1 (p < 0.01) and decreased acc-1 and fas (p < 0.05) in both OA + HF and MET + HF treated groups. Conclusions: The present study shows that neonatal oral administration of oleanolic acid and metformin potentially protects against the development of fructose-induced metabolic dysfunction in the rats in both short and long time periods.
Smartphone Continuous Authentication Using Deep Learning Autoencoders

Continuous authentication is receiving increased attention from providers of on-line services, particularly due to the ability of mobile apps to collect user-specific sensor data. However, the approaches proposed so far are either not accurate enough to provide a high-quality user experience or restricted by engineering challenges to capture data continuously. In this paper, we propose an approach based on a deep learning autoencoder, which achieves an equal error rate as low as 2:2% in tested real-world scenarios. The suggested system only relies on accelerometer data and does not require a high number of features, therefore reducing the computational burden. We discuss the balance between the number of dimensional features and the re-authentication time, which decreases as the number of dimensions increases. We also discuss parameter selection for real-world scenarios e.g. depth of the architecture, time elapsed before re-building the model and length of the training dataset and possible approaches to find the optimal trade-off between accuracy and usability required for each particular context.
Decay of internal reference information in duration discrimination: Intertrial interval modulates the Type B effect

Psychophysical evidence suggests that human perception of a stimulus is assimilated towards previous stimuli. The internal reference model (IRM) explains such assimilation through an internal reference (IR), which integrates past and present stimulus representations and thus might be conceived as a form of perceptual memory. In this study, we investigated whether the IR decays with time, as previously shown for perceptual memory representations in general. One specific prediction of IRM is higher discrimination sensitivity when a constant standard precedes rather than follows a variable comparison in a two-alternative forced-choice (2AFC) discrimination task. Furthermore, the magnitude of this so-called negative Type B effect should decrease with decreasing weighting of past stimulus information in the integration process. Therefore, decay of the IR should result in a reduced Type B effect. To examine this prediction, we carried out a 2AFC duration discrimination experiment with a short (1,600 ms) and a long (3,200 ms) intertrial interval (ITI). As expected, a reduced negative Type B effect was observed at the long compared with the short ITI, consistent with the idea that humans rely on the immediate past when evaluating current sensory input, however, less so when the IR incorporating the perceptual short-term memory representation of these past stimuli has already decayed.