Miracle-dz/UniFAR-FTUs huggingface dataset:
A Hybrid Optical Detection Algorithm for Plug-in Capacitor

In the process of circuit installation, plug-in components are usually installed manually. The characteristics of plug-in components are: a wide range of types, large size and irregular. So there are great difficulties in the optical automatic inspection of such components.In addition to the above features, the plug-in capacitor also has polarity. The polarity detection of plug-in capacitor is also very difficult.In this paper, a three-stage capacitor search algorithm based on YOLO target search is proposed to realize the recognition and location of plug-in capacitors. Then the hybrid feature comparison algorithm is used to judge the type of errors.Experiments show that the proposed algorithm can effectively recognize the plug-in capacitor. It can realize the detection of capacitor missing, opposite polarity and mismatch. It has good detection performance for capacitor missing and opposite polarity.
Objective Functions to Determine the Number of Topics for Topic Modeling

Topic modeling is a well-known task in unsupervised machine learning, where clustering algorithms are used to find latent topics. Several algorithms are presented in the literature, but the best known of them suffer from the drawback of requiring a lot of hyperparameter tuning to achieve good results. Especially, the number of latent topics or clusters (k) needs to be known in advance. In view of this situation, this paper analyses objective functions that help to evaluate the models in order to determine optimal hyperparameters. An empirical qualitative study was conducted using the NMF algorithm on different datasets to experimentally determine numerical properties of topic models which indicate an optimal k. Based on this study, we propose objective functions to select optimal topic models and discuss their results on different datasets.
Network Intrusion Detection Based on One-dimensional Convolution Layer Autoencoders

Intrusion detection technology is an active defense technology to ensure network security. Current intrusion detection models require a large amount of abnormal data to be trained. However, it is difficult to collect abnormal data in reality, and the collected data are normal. The work applied a one-dimensional convolutional layer to the encoder of the first half of the autoencoder model and designed a convolutional autoencoder-based network intrusion detection model to reduce the dependence of model training on abnormal data and increase the recall rate of abnormal data detection. The model only needed normal data for training, belonging to unsupervised learning. Finally, the KDD 99 data set was used for testing. The experimental results showed that the recall rate of this model for abnormal data detection had reached 100%, and compared with the ordinary fully connected layer autoencoder model, the robustness of the model was improved.
Radar Target Tracking Based on Firefly Intelligent Optimization Particle Filter Algorithm

Aiming at the problem of poor tracking accuracy in radar target tracking derived from particle filter (PF) under unknown measurement noise environment. In this research, the basic particle filter algorithm is improved, and the Firefly Algorithm (FA) is brought in the particle filter in order to displace the original resampling process, so that the particles move on to the high-likelihood area, avoiding the screening of particles, thereby overcoming particle poverty. It also improves the particle quality.In the modeling process, the measurement noise variance is estimated in real time using moving window technology to further ameliorate the correctness of radar target tracking. Finally, by simulating radar target tracking, the availability of the algorithm is proved.
Water Meter Reading Recognition Based on Lightweight CNN

In order to improve the accuracy of reading recognition in water meter image, a reading recognition method based on lightweight convolution neural network is proposed. The water meter image collected needs to be preprocessed by the methods of filtering, Hough circle detection, grayscale, edge detection, character area positioning and tilt correction. Then, a lightweight convolutional neural network consists of five convolution layers is proposed, which was confined to process the limited area of numeric characters in the water meter images. In addition, a certain number of 3×3, 1×3 and 3×1 convolutional layers were reconstructed from 3×3 and 5×5 structures to simplify the parameters and complexities of the model. In addition to improving the recognition accuracy, the features before asymmetric convolution were fused with that after asymmetric convolution. The experimental result shows that the training parameters are reduced greatly and the efficiency of training is improved significantly. And under the 3000 iterations, the recognition accuracy of this improved network is 98.85%, while the recognition accuracy of LeNet-5 network is only 97.11%.
Secrecy Performance for Hybrid RF/VLC DF Relaying Systems

This letter studies the security performance of hybrid radio frequency (RF) and visible light communication (VLC) system. In this hybrid system, the source node (i.e., Alice) transmits information to the relay node via the outdoor RF link. Nakagami-m fading and path loss are considered for the RF link. The relay using the decode-and-forward (DF) relaying scheme. A legitimate receiver (Bob) arranged on the floor receives the optical signal. An eavesdropper (Eve) deployed in VLC link wiretaps the confidential information. In this paper, secrecy outage probability (SOP) is used to assess the performance of the system. We derive the closed expression of the lower bound of SOP when VLC link is wiretapped. Numerical results to validate the accuracy of our derivation.
Twin Meander Coil

Energy-efficient and unconstrained wearable sensing platforms are essential for ubiquitous healthcare and activity monitoring applications. This paper presents Twin Meander Coil for wirelessly connecting battery-free on-body sensors to a textile-based reader knitted into clothing. This connection is based on passive inductive telemetry (PIT), wherein an external reader coil collects data from passive sensor coils via the magnetic field. In contrast to standard active sensing techniques, PIT does not require the reader to power up the sensors. Thus, the reader can be fabricated using a lossy conductive thread and industrial knitting machines. Furthermore, the sensors can superimpose information such as ID, touch, rotation, and pressure on its frequency response. However, conventional PIT technology needs a strong coupling between the reader and the sensor, requiring the reader to be small to the same extent as the sensors' size. Thus, applying this technology to body-scale sensing systems is challenging. To enable body-scale readout, Twin Meander Coil enhances the sensitivity of PIT technology by dividing the body-scale meander-shaped reader coils into two parts and integrating them so that they support the readout of each other. To demonstrate its feasibility, we built a prototype with a knitting machine, evaluated its sensing ability, and demonstrated several applications.
Design and development of embroidered textile electrodes for continuous measurement of electrocardiogram signals

Textile electrodes are a new and potential choice for long term and continuous monitoring of electrocardiogram measurements. In this research, textile electrodes have been designed and developed by embroidering conductive yarn on the polyester fabric to measure electrocardiogram biosignals of patients. Silver-coated nylon thread is embroidered on 100% polyester fabric in square form 11 mm × 11 mm with satin stitches in order to form three heart vectors (V3, V4, and V5). These electrodes are characterized based on electrode impedance and electrocardiogram measurement and the results are compared with the commercially available disposable Ag/AgCl electrodes. Further, additional tests have been performed using an electrode designed with 50% of the conductive thread used in the original sample. Real-time electrocardiogram signals, QRS-complex, P-wave, and T-wave were obtained for 10 subjects using existing hospital electrocardiogram equipment. The performance and repeatability of the electrode designed with 50% less conductive thread and effect of laundering were also studied. The results showed that the impedance of electrode has an acceptable value of 1.45 MΩ/cm2. Ageing tests showed that there is only a negligible deviation in the performance of the electrode. The results after laundering showed that the performance of the electrode is not affected by the laundering process.
Supervised Learning Algorithm Tempotron based on pulse Neural Network

Based on the pulse neural network, a simple SNN network is constructed by Tempotron to identify the MNIST data set. The first thing to consider is how to convert the MNIST data set into a pulse input using the gauss tuning curve encoder for Tempotron, which translates the input data into a pulse release time in parallel on the time dimension. For the impulse response model, once the input is given, the response equation of the Neuron is known, and the state of the Neuron can be solved at any time. The simulation results show that the Tempotron algorithm is similar to the perceptron in Ann and has certain classification ability.
A Hybrid Thresholding Strategy combining RCut and PCut for Multi-label Classification

Multi-label classification is a variant of the classification problem where multiple labels may be assigned to each instance. Usually multi-label classification algorithms output a numerical score for each label, indicative of their relevance to a query instance. However, in many applications the desired output is a bipartition of the labels into relevant and irrelevant w.r. t the query instance. Bipartitions can be obtained from scores using various thresholding strategies, such as PCut strategy which selects relevant instances per label, and RCut strategy which selects relevant labels per instance. However, we suggest that a combination of both strategies would provide better classification performance. In this paper, we propose a fuzzy-based approach to combine PCut and RCut strategies, by converting the crisp relevance into fuzzy one, merging them linearly, and defuzzifying again. Our experiments shows that our hybrid approach indeed outperforms both strategies.
The biota of Canada: checklist of the centipedes of Canada (Myriapoda: Chilopoda)

Abstract The centipede fauna of Canada is reviewed based on information available in the literature and on examination of some material, and provincial and territorial distributions are provided. About 53 species are known from Canada, representing four orders: Scutigeromorpha (1), Scolopendromorpha (5), Geophilomorpha (19), and Lithobiomorpha (28). British Columbia has the most recorded species (23), followed by Ontario (17) and Newfoundland and Labrador (12). Arctogeophilus glacialis (Attems) and Alaskobius adlatus Chamberlin are newly reported from Canada (Northwest Territories), Schendyla nemorensis (Koch) is newly reported from Ontario, and Lithobius forficatus (Linnaeus) is recorded for the first time from New Brunswick and Prince Edward Island. Arctogeophilus melanonotus (Wood) is removed from the list of Canadian species.
The Variability of Mental Timeline in Vertical Dimension

People often use concrete spatial terms to represent abstract time. Previous studies have shown that mental timeline (MTL) is represented along a horizontal axis. Studies of the mental timeline have demonstrated that compared with English speakers, Mandarin speakers are more likely to think about time vertically (up-down) than horizontally (left-right/front-back). Prior studies have suggested that MTL in the up and down dimensions originated from temporal-spatial metaphors in language. However, there are still a large number of perceptual experiences in the up and down dimensions, such as visual and sensorimotor experience. Then does the visual experience in daily life affect the MTL in the vertical dimension? This study is aimed to investigate whether visual experience can promote or activate the opposite direction of MTL from implicit and explicit levels. The results showed that when the time information in the task was not prominent, the direction of vertical MTL cannot be affected by ascending or descending perceptual experience. While when the time information was prominent, whether the task was implicit or explicit, compared with the control group, watching the top-down scene significantly increased the top-down direction selection, while in the implicit task, watching the bottom-up scene made the top-down MTL disappear. To the best of our knowledge, our study provides the first evidence that the flexibility of space–time associations in vertical dimension extends beyond explicit and embraces even implicit levels. This study shows that the vertical MTL is activated in certain conditions and could be affected by the visual experience.
A Two-Stage Adaptive Laboratory Evolution Strategy to Enhance Docosahexaenoic Acid Synthesis in Oleaginous Thraustochytrid

Thraustochytrid is a promising algal oil resource with the potential to meet the demand for docosahexaenoic acid (DHA). However, oils with high DHA content produced by genetic modified thraustochytrids are not accepted by the food and pharmaceutical industries in many countries. Therefore, in order to obtain non-transgenic strains with high DHA content, a two-stage adaptive laboratory evolution (ALE) strategy was applied to the thraustochytrid Aurantiochytrium sp. Heavy-ion irradiation technique was first used before the ALE to increase the genetic diversity of strains, and then two-step ALE: low temperature based ALE and ACCase inhibitor quizalofop-p-ethyl based ALE were employed in enhancing the DHA production. Using this strategy, the end-point strain E-81 with a DHA content 51% higher than that of the parental strain was obtained. The performance of E-81 strain was further analyzed by component analysis and quantitative real-time PCR. The results showed that the enhanced in lipid content was due to the up-regulated expression of key enzymes in lipid accumulation, while the increase in DHA content was due to the increased transcriptional levels of polyunsaturated fatty acid synthase. This study demonstrated a non-genetic approach to enhance lipid and DHA content in non-model industrial oleaginous strains.
Improving Operational Readiness of Airport Emergency Response Crews: Utilization of Gaming Theory in Decision Making Simulations

Author: William E. Vines Jr. Title: Improving Operational Readiness of Airport Emergency Response Crews: Utilization of Gaming Theory in Decision Making Simulations Institution: Embry-Riddle Aeronautical University Degree: Master of Aeronautical Science Year: 1995 The purpose of this study was to evaluate the potential effects of simulation gaming technique on the decision-making skills of airport emergency response technicians. Through the use of descriptive research methods this study has examined the benefits of using simulation training to enhance operational readiness. A specialized questionnaire was developed using a Likert scale format to attain the opinion of 20 airport directors—or their representatives. Findings did support the research hypothesis that the introduction of simulation training (Table Top) exercises would increase the operational readiness of airport emergency response crews. Statistical analysis of survey responses found that no significant difference occurred between answers provided by large airport staff and those provided by small airports.
Pre-operative Carboplatin/Paclitaxel Versus 5-Fluorouracil (5-FU)-based Chemoradiotherapy for Older Adults With Esophageal Cancer

Background/Aim: This study aimed to compare the efficacy and tolerability of pre-operative platinum/5-fluorouracil (P5F) and carboplatin/paclitaxel (CP), in combination with radiation therapy in older adults with locally advanced, stage I-III esophageal cancer. Patients and Methods: We retrospectively reviewed 51 patients aged ≥70 years who underwent chemoradiotherapy followed by esophagectomy for stage I-III esophageal cancer between 2008 and 2018. Pathological complete response (pCR) and survival rates were compared across the two chemotherapy regimen arms. Results: Treatment completion (p=0.28), pCR (p=0.89), and partial response rates were similar across both chemotherapy groups. Overall survival (OS) and disease-free survival (DFS) were similar across both groups with HR=0.80 (p=0.62) and HR=0.72 (p=0.72) respectively. Conclusion: The lesser toxic CP regimen may be used in older patients with locally advanced esophageal cancer, with tumor response and survival rates similar to P5F chemotherapy.
Inner Workings: Using vaccines to harness the immune system and fight drugs of abuse

Opioids continue to ravage large swaths of the United States. Buffeted by social isolation, financial pressures, and limited mental health resources during the coronavirus disease 2019 (COVID-19) pandemic, addiction and its ill effects have only worsened in the past year. More than 100,000 people died from drug overdose between April 2020 and the end of April 2021, a roughly 30% increase in deaths compared with the previous year and an all-time high for the number of overdose deaths recorded in the United States. About three-quarters of those deaths resulted from synthetic opioid abuse. And yet, few medical treatments are available for those experiencing opioid and other severe substance abuse disorders. Individuals addicted to opioids can wean off these drugs using methadone or buprenorphine, which offer opioid replacement—a safer variation of the drug that doesn’t cause a high or lead to an overdose. And naltrexone, an opioid antagonist, blocks the opioid receptors. But these treatments have drawbacks and are not effective for everyone, especially long-term. In the next few years, however, those seeking treatment may find help from a surprising source: their own immune system. Researchers are developing vaccines that would stimulate the production of antibodies to destroy opioid molecules before they ever reach the brain, thus blocking both the high and the potential for overdose. Right now, the first vaccine against opioid painkillers is working its way through early clinical trials at the New York State Psychiatric Institute. The idea of using vaccines against drugs of abuse has been around for decades—researchers initially targeted nicotine and cocaine. Thus far, research into these sorts of inoculations has seen little success. Nevertheless, the notion has started to attract attention in recent years; the NIH has been channeling funds into opioid vaccine research since 2018 through the HEAL Initiative (Helping to End Addiction Long-term). The infusion of grants has brought a much-needed boost to the field. And increased attention to vaccines owing to the pandemic— as well as interest in lab-engineered monoclonal antibodies—has buoyed the notion of vaccinating against addiction, perhaps making it a viable option in the foreseeable future. Of course, a multitude of challenges remain, not all of which entail crafting a vaccine that effectively
The Association of the Lymphocyte-to-C-Reactive-Protein Ratio With Gastric Cancer Patients Who Receive Curative Treatment

Background/Aim: We investigated the association of the preoperative lymphocyte-to-C-reactive-protein ratio (LCR) with gastric cancer survival and recurrence after curative treatment. Patients and Methods: This study included 480 patients who underwent curative surgery followed by adjuvant treatment for gastric cancer between 2013 and 2017. The prognostic factors for overall survival (OS) and recurrence-free survival (RFS) were identified. Results: A LCR of 7,000 was regarded as the optimal critical point of classification, considering the 1-, 3- and 5-year survival rates. The OS rates at 3 and 5 years after surgery were 84.4% and 73.9% in the low-LCR group, respectively, and 92.4% and 87.0% in the high-LCR group, respectively, and were statistically significantly different. The RFS rates at 3 and 5 years after surgery were 78.8% and 68.7% in the low-LCR group, respectively, and 89.3% and 86.6% in the high-LCR group, respectively, with a statistically significant difference. A multivariate analysis showed that the LCR was a significant independent prognostic factor for both OS and RFS. Conclusion: The LCR was a significant prognostic factor for survival in patients who underwent curative treatment for gastric cancer.
Specific absorption rate and temperature increases in the head of a cellular-phone user

In this paper, a complete electromagnetic and thermal analysis has been performed considering the head of a subject exposed to various kinds of cellular phones available on the market, and focusing the attention on important organs like the eye lens and brain. Attention has first been posed on a particular phone model, and a comparison between the absorbed power distribution and steady-state temperature increases has been carried out. The influence of different antennas (dipole, monopole, whip, and planar inverted F antenna) on the power absorption and on the consequent tissue heating has then been analyzed. The obtained results show for a radiated power of 600 mW, maximum SAR values, averaged over 1 g, from 2.2 to 3.7 W/kg depending on the considered phone. The maximum temperature increases are obtained in the ear and vary from 0.22/spl deg/C to 0.43/spl deg/C, while the maximum temperature increases in the brain lie from 0.08/spl deg/C to 0.19/spl deg/C. These steady-state temperature increases are obtained after about 50 min of exposure, with a time constant of approximately 6 min. Finally, the results evidence a maximum temperature increase in the external part of the brain from 0.10/spl deg/C to 0.16/spl deg/C for every 1 W/kg of SAR, averaged over 1 g of brain tissue.
Restoration of Homeostasis in the Tracheal Mucosa After Thyroid Surgery in a Rat Model

Background/Aim: This study aimed to investigate the process of homeostatic restoration in the tracheal mucosa (TM) after thyroid surgery. Materials and Methods: Fifty-four rats were divided into normal controls (NC) and three experimental groups: (i) flap elevation (FE), (ii) thyroid exposure (TE), and (iii) thyroid isthmusectomy (TI). Expression of mRNA and proteins of key factors regulating homeostasis were evaluated in the TM obtained 3, 7, and 21 days after thyroid surgery. Results: Increased mRNA expression of transforming growth factor-β1 (TGF-β1), hypoxia-inducible factor-1α (HIF-1α), and matrix metalloproteinase-9 (MMP-9) were observed 21 days after thyroid surgery in all experimental groups compared to that of NC group. Conclusion: Thyroid surgery leads to an actual increase of TGF-β1, HIF-1α, and MMP-9 expression in the TM. This increased expression of key regulators of homeostatic restoration in the TM lasts for a considerable period of time after surgery, especially if the extent of surgery increased.