False Labeling Research Articles

Rapid identification of Takifugu genus using visual loop-mediated isothermal amplification.

Some Takifugu species are commonly found in the coastal areas of China, Japan, Thailand, and Korea and cause pufferfish poisoning, which is toxic and even lethal to humans. From 2010 to 2015, there were 430 cases of pufferfish poisoning worldwide, resulting in 52 deaths. Identification of Takifugu species is imperative to reduce financial losses and ensure food safety. Here, visual loop-mediated isothermal amplification (LAMP) was applied to identify Takifugu species. Conserved regions within the mitochondrial DNA among different Takifugu species were selected to design LAMP primers. In 55min of amplification, sufficient DNA was obtained to observe the results with the naked eye, without the need for complicated instruments. The method was highly specific, with no cross-detection of 17 other fish species, namely, 7 Tetraodontiformes species and 10 commercially important fish. The method showed a detection limit of 0.1ng Takifugu DNA and was successfully validated to detect Takifugu in cooked fish and the vomitus of poisoned patients. This rapid and visual LAMP method is a useful tool to prevent false labeling, protect consumer rights, and reduce the risk of pufferfish poisoning. PRACTICAL APPLICATION: The loop-mediated isothermal amplification method established in this study can identify cooked or digested fish products containing 1% or more of Takifugu. Therefore, it can be used for the visual detection of Takifugu products and the medical diagnosis of Takifugu poisoning.

Abir's Enlightenment Revolution is the basic element leading to the end of the corrupt regime resulting from the poisoned Tunisian revolution 2011

Ten years after the launch of its 2011 revolution, Tunisia has reached a catastrophic socio-economic situation that confirms that none of major goals of this revolution have been achieved. Here, from an anthropological analysis of major events happened during this decade I reveal and discuss mysteries of this revolution, and I show how and why it got to her final stage. I qualified it as „poisoned‟ because of clandestine interventions from some foreign countries that were able to steer it on a corrupt and dangerous path from the very beginning. In fact, although it was started by young people who have no political and ideological affiliation, many opportunist politicians rode its wave and given a false revolutionary label to their parties. One of these parties, „Ennahdha‟, in a clear relationship with some countries, very likely got secretly considerable funds. The use of these moneys, coupled with dissemination of religious misinformation, during the pre-elections period permitted this party to be the first to come to power. Since then, it began (1) to support secretly those who perform the corrupt instrumentalization of Islam leading to terrorism and obscurantism, (2) not to apply laws that conflict with its interests, and (3) to develop corruption through wide networks spread in most of the national institutions particularly in judicial and security sectors. This has ensured it permanent influence over the major joints of the State even if it does not have the highest representation in the Government. At the end of this despaired decade, a glimmer of hope appeared with the emergence of the wonderful leader ‟Abir Moussi‟ who called for Enlightenment Revolution. Her heroic struggle is the basic element leading to the end of the poisoned revolution 2011 and the resulting corrupt regime, which was mainly fabricated and dominated by Ennahdha, the last dangerous stronghold of the World Brotherhood Sect. I end this study by presenting recommendations aimed at eliminating the corrupt instrumentalization of Islam and preventing its return.

The Establishment of a Clinic for Personality Modulation in Iran: A Novel Approach in Personality Psychiatry with a Dimensional Approach

The Establishment of a Clinic for Personality Modulation in Iran: A Novel Approach in Personality Psychiatry with a Dimensional Approach

A Reliable Artificial Intelligence Model for False News Detection Made by Public Figures

The quick access to information on social media networks as well as its exponential rise also made it difficult to distinguish among fake information or real information. The fast dissemination by way of sharing has enhanced its falsification exponentially. It is also important for the credibility of social media networks to avoid the spread of fake information. So it is emerging research challenge to automatically check for misstatement of information through its source, content, or publisher and prevent the unauthenticated sources from spreading rumours. This paper demonstrates an artificial intelligence based approach for the identification of the false statements made by social network entities. Two variants of Deep neural networks are being applied to evalues datasets and analyse for fake news presence. The implementation setup produced maximum extent 99% classification accuracy, when dataset is tested for binary (true or false) labeling with multiple epochs.

A novel algorithm for 3-D visualization of electrogram duration for substrate-mapping in patients with ischemic heart disease and ventricular tachycardia.

BackgroundMyocardial slow conduction is a cornerstone of ventricular tachycardia (VT). Prolonged electrogram (EGM) duration is a useful surrogate parameter and manual annotation of EGM characteristics are widely used during catheter-based ablation of the arrhythmogenic substrate. However, this remains time-consuming and prone to inter-operator variability. We aimed to develop an algorithm for 3-D visualization of EGM duration relative to the 17-segment American Heart Association model.MethodsTo calculate and visualize EGM duration, in sinus rhythm acquired high-density maps of patients with ischemic cardiomyopathy undergoing substrate-based VT ablation using a 64-mini polar basket-catheter with low noise of 0.01 mV were analyzed. Using a custom developed algorithm based on standard deviation and threshold, the relationship between EGM duration, endocardial voltage and ablation areas was studied by creating 17-segment 3-D models and 2-D polar plots.Results140,508 EGMs from 272 segments (n = 16 patients, 94% male, age: 66±2.4, ejection fraction: 31±2%) were studied and 3-D visualization of EGM duration was performed. Analysis of signal processing parameters revealed that a 40 ms sliding SD-window, 15% SD-threshold and >70 ms EGM duration cutoff was chosen based on diagnostic odds ratio of 12.77 to visualize rapidly prolonged EGM durations. EGMs > 70 ms matched to 99% of areas within dense scar (<0.2 mV), in 95% of zones within scar border zone (0.2–1.0 mV) and detected ablated areas having resulted in non-inducibility at the end of the procedure. Ablation targets were identified with a sensitivity of 65.6% and a specificity of 94.6% avoiding false positive labeling of prolonged EGMs in segments with healthy myocardium.ConclusionThe novel algorithm allows rapid visualization of prolonged EGM durations. This may facilitate more objective characterization of arrhythmogenic substrate in patients with ischemic cardiomyopathy.

Your mother was right, washing matters: An alkyne-analog of ibuprofen reveals unwanted reactivity of aromatic compounds with proteins during copper-catalyzed click chemistry

Bioorthogonal chemistry, in particular the copper(I)-catalyzed azide-alkyne cycloaddition (CuAAC), has enabled the robust identification of covalent protein targets of probes and drugs. Ibuprofen is commonly used pain and fever reducer and is sold as an enantiomeric racemate. Interestingly, the stereoisomers can be enzymatically converted through an ibuprofen-CoA thioester intermediate, which might non-specifically react with protein nucleophiles. Here, we use an alkyne-analog of ibuprofen to make two discoveries. First, we find that ibuprofen likely does not result in notable chemical labeling of proteins. However, we secondly find that aromatic compounds can react with proteins during the CuAAC reaction unless they are appropriately washed out of the mixture. This second discovery of false positive labeling has important technical implications for the application of this approach.

Pengaruh Algoritma ADASYN dan SMOTE terhadap Performa Support Vector Machine pada Ketidakseimbangan Dataset Airbnb

Traveling activities are increasingly being carried out by people in the world. Some tourist attractions are difficult to reach hotels because some tourist attractions are far from the city center, Airbnb is a platform that provides home or apartment-based rentals. In lodging offers, there are two types of hosts, namely non-super host and super host. The super-host badge is obtained if the innkeeper has a good reputation and meets the requirements. There are advantages to being a super host such as having more visibility, increased earning potential and exclusive rewards. Support Vector Machine (SVM) algorithm classification process by these criteria data. Data set is unbalanced. The super host population is smaller than the non-super host. Overcoming the imbalance, this over sampling technique is carried out using ADASYN and SMOTE. Research goal was to decide the performance of ADASYN and sampling technique, SVM algorithm. Data analyses used over sampling which aims to handle unbalanced data sets, and confusion matrix used for testing Precision, Recall, and F1-SCORE, and Accuracy. Research shows that SMOTE SVM increases the accuracy rate by 1 percent from 80% to 81%, which is influenced by the increase in the True (minority) label test results and a decrease in the False label test results (majority), the SMOTE SVM is better than ADASYN SVM, and SVM without over sampling.

Investigation of the characteristics of different shrimps by species and habitat using gas chromatography/mass spectrometry based metabolomics

Approximately 6.5 million tons of shrimp are consumed annually worldwide. The price of shrimp is greatly influenced by species and habitat (e.g., farmed vs wild-caught). In recent years, false labeling has become a problem in the shrimp industry. False labeling can include species, habitat (whether farmed or wild-caught). This problem is motivated by the potential for economic benefit, and significantly reduces the consumer reliability of food. As a first step in establishing a detection method, we took a metabolomics approach to elucidate phenotypic diversity by assessing genetic differences and environmental factors. Metabolites identified by gas chromatography/mass spectrometry (GC/MS) analysis were subjected to multivariate analysis to identify metabolites that correlated with shrimp species and habitat. The characteristics based on species and habitat were observed respectively. For species, the classification approximately tended to be based on taxonomy. It suggests that species different have strong effect on metabolite profiles. In particular, the difference between Panaediae and Pandalidae was significantly observed, and some fatty acids such as palmitoleic acid and elaidic acid are abundant in Pandalidae. Among Pandalidae, Japanese tiger shrimp was characterized by metabolites related to purine metabolism. For habitat, farmed shrimp had a high amino acid content, and wild caught shrimp had a high fatty acid content. Habitat-based separation was observed in Indonesian black tiger shrimp samples, indicating that metabolites such as glycolic acid, phosphate, and pentadecanoic acid are characteristic components of natural black tiger shrimp.

Some Examples of the Use of Molecular Markers for Needs of Basic Biology and Modern Society.

Simple SummaryThe main issues of the report are focused on four items. (1) A combination of nDNA and mtDNA markers best suits the hybrid identification and estimates of genetic introgression between different biological species. (2) The available facts on nDNA and mtDNA diversity seemingly make obvious the introgression presence among many taxa, although, it is evident that introgression may be quite restricted or asymmetric, thus holding at least the “source” taxon (taxa) intact. (3) If we accept that sexually reproducing species in marine and terrestrial realms are introgressed, as it is still evident for many cases, then we should recognize that the biological species concept, in terms of complete lack of gene flow among species, is inadequate due to the fact, that many zoological species are not biological species yet. However, vast modern molecular data proved that with time they definitely become biological species. (4) The recent investigation of fish taxa divergence using central DNA barcoding database shows that most gene trees are, basically, appeared monophyletic and interspecies reticulations are rare.Application of molecular genetic markers appeared to be very fruitful in achieving many goals, including (i) proving the theoretic basements of general biology and (ii) assessment of worldwide biodiversity. Both are provided in the present meta-analysis and a review as the main signal. One of the basic current challenges in modern biology in the face of new demands in the 21st century is the validation of its paradigms such as the synthetic theory of evolution (STE) and biological species concept (BSC). Another of most valuable goals is the biodiversity assessment for a variety of social needs including free web-based information resources about any living being, renovation of museum collections, nature conservation that recognized as a global project, iBOL, as well as resolving global trading problems such as false labeling of species specimens used as food, drug components, entertainment, etc. The main issues of the review are focused on animals and combine four items. (1) A combination of nDNA and mtDNA markers best suits the identification of hybrids and estimation of genetic introgression. (2) The available facts on nDNA and mtDNA diversity seemingly make introgression among many taxa obvious, although it is evident, that introgression may be quite restricted or asymmetric, thus, leaving at least the “source” taxon (taxa) intact. (3) If we consider sexually reproducing species in marine and terrestrial realms introgressed, as it is still evident in many cases, then we should recognize that the BSC, in view of the complete lack of gene flow among species, is inadequate because many zoological species are not biological ones yet. However, vast modern molecular data have proven that sooner or later they definitely become biological species. (4) An investigation into the fish taxa divergence using the BOLD database shows that most gene trees are basically monophyletic and interspecies reticulations are quite rare.

Image Enhanced Mask R-CNN: A Deep Learning Pipeline with New Evaluation Measures for Wind Turbine Blade Defect Detection and Classification.

Demand for wind power has grown, and this has increased wind turbine blade (WTB) inspections and defect repairs. This paper empirically investigates the performance of state-of-the-art deep learning algorithms, namely, YOLOv3, YOLOv4, and Mask R-CNN for detecting and classifying defects by type. The paper proposes new performance evaluation measures suitable for defect detection tasks, and these are: Prediction Box Accuracy, Recognition Rate, and False Label Rate. Experiments were carried out using a dataset, provided by the industrial partner, that contains images from WTB inspections. Three variations of the dataset were constructed using different image augmentation settings. Results of the experiments revealed that on average, across all proposed evaluation measures, Mask R-CNN outperformed all other algorithms when transformation-based augmentations (i.e., rotation and flipping) were applied. In particular, when using the best dataset, the mean Weighted Average (mWA) values (i.e., mWA is the average of the proposed measures) achieved were: Mask R-CNN: 86.74%, YOLOv3: 70.08%, and YOLOv4: 78.28%. The paper also proposes a new defect detection pipeline, called Image Enhanced Mask R-CNN (IE Mask R-CNN), that includes the best combination of image enhancement and augmentation techniques for pre-processing the dataset, and a Mask R-CNN model tuned for the task of WTB defect detection and classification.

Correcting and reweighting false label masks in brain tumor segmentation.

Recently, brain tumor segmentation has made important progress. However, the quality of manual labels plays an important role in the performance, while in practice, it could vary greatly and in turn could substantially mislead the learning process and decrease the accuracy. We need to design a mechanism to combine label correction and sample reweighting to improve the effectiveness of brain tumor segmentation. We propose a novel sample reweighting and label refinement method, and a novel three-dimensional (3D) generative adversarial network (GAN) is introduced to combine these two models into an united framework. Extensive experiments on the BraTS19 dataset have demonstrated that our approach obtains competitive results when compared with other state-of-the-art approaches when handling the false labels in brain tumor segmentation. The 3D GAN-based approach is an effective approach to handle false label masks by simultaneously applying label correction and sample reweighting. Our method is robust to variations in tumor shape and background clutter.

An adaptive background modeling for foreground detection using spatio-temporal features

Background modeling is a well accepted foreground detection technique for many visual surveillance applications like remote sensing, medical imaging, traffic monitoring, crime detection, machine/robot vision etc. Regardless of simplicity of foreground detection concept, no conventional algorithms till date seem to be able to concurrently address the key challenges like illumination variation, dynamic background, low contrast and noisy sequences. To mitigate this issue, this paper proposes an improved scheme for foreground detection particularly addresses all the aforementioned key challenges. The suggested scheme operates as follows: First, a spatio-temporal local binary pattern (STLBP) technique is employed to extract both spatial texture feature and temporal motion feature from a video frame. The present scheme modifies the change detection rule of traditional STLBP method to make the features robust under challenging situations. The improvisation in change description rule reflects that to extract STLBP features, the mean of the surrounding pixels is chosen instead of a fixed center pixel across a local region. Further, in many foreground detection algorithms a constant learning rate and constant threshold value is considered during background modeling which in turn fails to detect a proper foreground under multimodal background conditions. So to address this problem, an adaptive formulation in background modeling is proposed to compute the learning rate (αb) and threshold value (Tp) to detect the foreground accurately without any false labeling of pixels under challenging environments. The performance of the proposed scheme is evaluated through extensive simulations using different challenging video sequences and compared with that of the benchmark schemes. The experimental results demonstrate that the proposed scheme outperforms significant improvements in terms of both qualitative as well as quantitative measures than that of the benchmark schemes.

食品偽装問題 : 生協での事例と対応について(テーマ:偽装表示はなぜ起きるのか-信頼できる食品表示のあり方を求めて-,2008年度大会ミニシンポジウム報告)

食品偽装問題 : 生協での事例と対応について(テーマ:偽装表示はなぜ起きるのか-信頼できる食品表示のあり方を求めて-,2008年度大会ミニシンポジウム報告)

座長解題・総括(テーマ:偽装表示はなぜ起きるのか-信頼できる食品表示のあり方を求めて-,2008年度大会ミニシンポジウム報告)

座長解題・総括(テーマ:偽装表示はなぜ起きるのか-信頼できる食品表示のあり方を求めて-,2008年度大会ミニシンポジウム報告)

韓国における食品安全に関する制度と課題 : 米国産牛肉輸入問題と原産地表示制度を中心に(テーマ:偽装表示はなぜ起きるのか-信頼できる食品表示のあり方を求めて-,2008年度大会ミニシンポジウム報告)

韓国における食品安全に関する制度と課題 : 米国産牛肉輸入問題と原産地表示制度を中心に(テーマ:偽装表示はなぜ起きるのか-信頼できる食品表示のあり方を求めて-,2008年度大会ミニシンポジウム報告)

Chemical Fingerprinting of Olive Oils by Electrospray Ionization-Differential Mobility Analysis-Mass Spectrometry: A New Alternative to Food Authenticity Testing.

Recently, the olive oil industry has been the subject of harsh criticism for false labeling and even adulterating olive oils. This situation in which both the industry and the population are affected leads to an urgent need to increase controls to avoid fraudulent activities around this precious product. The aim of this work is to propose a new analytical platform by coupling electrospray ionization (ESI), differential mobility analysis (DMA), and mass spectrometry (MS) for the analysis of olive oils based on the information obtained from the chemical fingerprint (nontargeted analyses). Regarding the sample preparation, two approaches were proposed: (i) sample dilution and (ii) liquid-liquid extraction (LLE). To demonstrate the feasibility of the method, 30 olive oil samples in 3 different categories were analyzed, using 21 of them to elaborate the classification model and the remaining 9 to test it (blind samples). To develop the prediction model, principal component analysis (PCA) and orthogonal partial least-squares discriminant analysis (OPLS-DA) were used. The overall success rate of the classification to differentiate among extra virgin olive oil (EVOO), virgin olive oil (VOO), and lampante olive oil (LOO) was 89% for the LLE samples and 67% for the diluted samples. However, combining both methods, the ability to differentiate EVOO from lower-quality oils (VOO and LOO) and the edible oils (EVOO and VOO) from nonedible oil (LOO) was 100%. The results show that ESI-DMA-MS can become an effective tool for the olive oil sector.

A computer vision based rebar detection chain for automatic processing of concrete bridge deck GPR data

Manual processing of Ground Penetrating Radar (GPR) images is a very time-intensive task. The authors proposed a novel computer vision-based method for automatic detection of rebars in complex GPR images in highly deteriorated concrete bridge decks. The proposed detection model consists of a fine-tuned Histogram of Oriented Gradients feature descriptor, a Multi-Layer Perceptron for classification, and a post processing algorithm for eliminating false detections and labeling rebar in Region of Interest. State-of-art results are obtained on testing the method on real bridge deck GPR data and comparing the results with RADAN software. Overall accuracy of 89.4% is obtained on URIGPRv1.0 dataset, which is introduced in this paper. The proposed method is 54.35% more accurate comparing to the results obtained by RADAN software. The proposed classifier outperformed accuracy of a 3-layer convolutional neural network by 11.9%.

Allergological Study of 565 Elderly Patients Previously Labeled as Allergic to Penicillins.

PurposeElderly people thought to have an allergy to beta-lactams (BLs) may tolerate the drugs in subsequent exposures due to initial false labeling of allergies, the spontaneous loss of sensitivity to BLs over time or age-related decline in sensitization. As a result, they may be treated with less appropriate antibiotics, causing more side effects and entailing increased costs for health systems. The aim of this investigation was to assess whether patients in the third and fourth age with previously confirmed allergies to BLs had lost sensitization and could tolerate these antibiotics.Patients and methodsPatients allergic to BLs were divided into group A (aged 60–79 years) and B (aged ≥80 years). Clinical history, skin testing, drug challenge tests (DCT) and evaluation of resensitization were used to classify participants as showing immediate reactions, non-immediate reactions, or tolerance. We compared clinical entities, drugs involved, and final outcome by age group.ResultsOf 1362 cases evaluated, 565 underwent an allergological study. The skin was the most common organ involved. Anaphylaxis and side chain reactions were more frequent in group A (p<0.01), as were positive DCT. Classical benzylpenicillin determinants (benzylpenicilloyl and/or minor determinant mixture) were more frequent triggers in group B (p< 0.01). Resensitization after challenge occurred in very few participants.ConclusionThe risk for allergy to BLs decreases with age and a history of anaphylaxis by BLs is a predictor of positive results in skin tests (ST). Both immunoglobin E (IgE) and T-cell–mediated responses can disappear in elderly people, who can develop tolerance to these antibiotics. These results are of clinical relevance to patients who need to be treated with antibiotics from this family.

1131. Prevalence and Characteristics of Non-β-Lactam Allergy Labeling at a Children’s Hospital

BackgroundLimited data are available on non-β-lactam (NBL) antibiotic allergy labeling in children. Understanding the incidence and patterns of NBL labeling is important as NBL hypersensitivity testing lacks standardization and false labeling may constrain therapeutic options and compromise antimicrobial stewardship.MethodsWe conducted a retrospective review of patients at our tertiary care pediatric facility and associated clinics who had first reported allergy to NBL antibiotics from January 1, 2015 to December 31, 2015. Demographic data, NBL subclass, severity, description of reaction, and ICD-9/10 diagnostic codes were recorded. In addition, subsequent antibiotic during the following 3 years (2016–2018) was determined. NBL allergy descriptions, when reported, were categorized based on severity and type of reaction.ResultsOf 35,796 patients with first clinical encounters in 2015, 223 patients (0.6%) had at least one NBL allergy reported, 1370 (3.8%) had a β-lactam allergy reported, and 101 (0.3%) patients had both an NBL and β-lactam allergy. There were 16 patients with two NBL allergies. The median age of patients with NBL allergy was 9.0 years. NBL classes and allergic reaction types are listed in the tables. Chronic conditions of patients with NBL allergy included gastrointestinal disease (n = 51), neurological disease (n = 37), malignancy (n = 36), bone marrow or solid-organ transplant (n = 4), and cystic fibrosis (n = 5). In the subsequent 3 years, 28 patients with NBL allergies received 129 systemic courses of antibiotics as inpatients, including 8 patients who received ≥10 courses.ConclusionAlthough not as common as β-lactam allergies, NBL allergies were noted in a substantial number of new patients. When described, the majority of patients did not have severe reactions, and were most likely nonallergic adverse reactions. As many of the patients have chronic conditions and require subsequent antibiotics, adjudication of true allergy status may be beneficial. Disclosures All authors: No reported disclosures.

Recent developments and highlights in drug hypersensitivity.

Drug hypersensitivity reactions (DHRs) are nowadays the third cause of allergy after rhinitis and asthma with a significant increase in prevalence in both adults and paediatric population with new drugs included as culprit. For this, DHRs represent not only a health problem but also a significant financial burden for affected individuals and health systems. Mislabelling DHRs is showing to be a relevant problem for both, false label of drug allergic and false label of nonallergic. All this reinforces the need to improve accurate diagnostic approaches that allow an appropriate management. Moreover, there is a need for training both, nonallergist stakeholders and patients to improve the reaction identification and therefore decrease the mislabelling. The use of allergy cards has shown to be relevant to avoid the induction of DHRs due to the prescription of wrong medication. Recent developments over the last 2years and highlights about risk factors, diagnostic approaches, mechanisms involved as well as prevention actions, and management have been reviewed. In these papers, it has been outlined the need for correct diagnosis and de-labelling of patients previously false-reported as allergic, which will improve the management and treatment of patients with DHRs.