Miracle-dz/UniFAR-FTUs huggingface dataset:
Pectobacterium and Dickeya Responsible for Potato Blackleg Disease in New York State in 2016.

Beginning in 2014, outbreaks of blackleg disease compromised potato (Solanum tuberosum) production in the northeastern United States. Disease severity was atypical for plantings with certified seed. During 2016, 43 samples with blackleg symptoms were analyzed, originating from more than 20 farms operating in New York State. A combination of techniques was employed to identify the blackleg pathogens: isolation in vitro, diagnostic PCR assays for Pectobacterium and Dickeya sp. , pathogenicity assays, and DNA sequencing. Twenty-three bacterial isolates were obtained, the majority of which were designated D. dianthicola or P. parmentieri; two of the isolates were designated P. atrosepticum. All isolates were pathogenic in stem lesion and tuber soft rot assays and exhibited pectin degrading activity (pitting) in crystal violet pectate agar medium. Phylogenetic analyses of dnaX gene sequences placed all but one of the isolates into clades corresponding to D. dianthicola, P. parmentieri, or P. atrosepticum. One atypical isolate clustered with P. carotovorum subspecies. Data are consistent with the hypothesis that D. dianthicola from New York and the northeast are part of a single clade, and at least three different soft rot bacteria were associated with blackleg during 2016 in New York.
Downregulation of ERBB3 decreases the proliferation, migration and invasion of cervical cancer cells though the interaction with MTK-1

Cervical cancer is a common malignancy in females. Diagnosis and treatment of cervical cancer remains a challenge due to difficulties in the presence of tumor metastasis. Increased expression level of Erb-b2 receptor tyrosine kinase 3 (ERBB3) has previously been demonstrated to be associated with the occurrence of cervical cancer; however, the functionality of ERBB3 in the development of cervical cancer remains incompletely understood. In the present study, the expression level of ERBB3 in patients with cervical squamous cell carcinoma and cervical adenocarcinoma was detected by reverse transcription quantitative polymerase chain reaction. The effects of ERBB3 small interfering RNA silencing on cell proliferation, migration and invasion were explored, and the interaction between ERBB3 and mitogen-activated protein kinase kinase kinase 4 (MTK-1) was also investigated. It was identified that the downregulation of ERBB3 significantly decreased the proliferative, migratory and invasive abilities of cervical cancer cells. In addition, the expression level of MTK-1 was also significantly decreased following MTK-1 siRNA silencing. Therefore, we hypothesize that the downregulation of ERBB3 may decrease the proliferative, migratory and invasive abilities of cervical cancer cells by inhibiting the expression of MTK-1.
MSCS: MeshStereo with Cross-Scale Cost Filtering for fast stereo matching

MeshStereo (MS) and cross-scale cost filtering (CSCF) are two most recently celebrated models for stereo matching. On one hand, MS model enlightens for fast solving the dense stereo correspondence problem according to a region-based opinion. On the other hand, CSCF model could generate more robust matching cost volumes than single scale. In this study, the authors weave these two models together for attaining greater and faster disparity estimation. With CSCF, more powerful initial volumes of matching cost are computed and they are conducted as the data term of MS energy function model. More importantly, the novel-fused stereo model also draws a closer connection between multi-scale aggregated and global algorithms. Integrating the advantages of both stereo models, they name the presented one as MS with cross-scale (MSCS). Performance evaluations on Middlebury v.2 and v.3 stereo data sets demonstrate that the proposed MSCS outperforms other four most challenging stereo matching algorithms; and also performs better on Microsoft i2i stereo videos. In addition, thanks to this novel-fused model, MSCS requires fewer iteration times for optimising and makes it surprisingly possesses a much faster execution time.
Role of regulatory T cells and CD8+ T lymphocytes in the dissemination of circulating tumor cells in primary invasive breast cancer

Circulating tumor cells (CTCs) dissemination is involved in tumor metastasis and is an independent prognostic factor in patients with primary and metastatic breast cancer. Regulatory T cells (Tregs) and cluster of differentiation (CD)8+ T lymphocytes are the main types of immune cells in the tumor microenvironment and exert opposite roles on the progression and outcome of breast cancer. The aim of the present study was to evaluate the associations between CTCs and intratumoral/peritumoral Tregs and CD8+ T lymphocytes in breast cancer. Peripheral CTCs were detected by a multi-marker quantitative polymerase chain reaction platform in 167 patients with invasive breast cancer. Intratumoral/peritumoral Tregs and CD8+ T lymphocytes were assessed by immunohistochemistry in 167 patients with invasive breast cancer to establish an association between these cell types and detection of peripheral CTCs. CTCs were detected in 55% of the patients with breast cancer. The prevalence of CTCs was positively associated with the number of intratumoral (P=0.002) and peritumoral Tregs (P=0.045), and the primary tumor size (P=0.012). This result was verified by analyzing intratumoral Tregs (P=0.044) and primary tumor size (P=0.044) with multivariate analysis, which indicated that the CTC-positive rate increased with an increasing number of intratumoral Tregs and a larger tumor size In the multivariate analysis, other variables including menopause, tumor-node-metastasis stage and peritumoral Tregs were not associated with the prevalence of CTCs. The prevalence of CTCs was inversely and weakly associated with the number of peritumoral CD8+ T lymphocytes using the univariate analysis, however this result was not statistically significant (P=0.470). In conclusion, regulatory T cells and CD8+ T lymphocytes may be involved, at least in part, in the CTCs dissemination of breast cancer, whereby Tregs appear to exert the dominant effect. Furthermore, the role of Tregs in the progression of breast cancer may be mediated by suppressing the dissemination of CTCs, which is primarily determined by intratumoral Tregs.
Validity and reliability of evaluating hip abductor strength using different normalization methods in a functional electromechanical device

The hip abductor muscles are vitally important for pelvis stability, and common strength deficits can negatively affect functionality. The muscle strength can be measured using different dynamometers and be evaluated in three positions (side-lying, standing, and supine). Obtained strength data can be expressed in different ways, with data normalization providing more objective and comparable results. The aim of this study was to establish the validity and reliability of three protocols in evaluating the isometric strength of the hip abductor muscles. A new functional electromechanical dynamometer assessed strength in three positions, with findings subjected to three data normalization methods. In two identical sessions, the hip abductor strengths of 29 subjects were recorded in the side-lying, standing, and supine positions. Peak force was recorded in absolute terms and normalized against body mass, fat-free mass, and an allometric technique. The peak force recorded in the side-lying position was 30% and 27% higher than in the standing and supine positions, respectively, independent of data normalization methodology. High inter-protocol correlations were found (r: 0.72 to 0.98, p ≤ 0.001). The supine position with allometric data normalization had the highest test-retest reliability (0.94 intraclass correlation coefficient and 5.64% coefficient of variation). In contrast, the side-lying position with body mass data normalization had a 0.66 intraclass correlation coefficient and 9.8% coefficient of variation. In conclusion, the functional electromechanical dynamometer is a valid device for measuring isometric strength in the hip abductor muscles. The three assessed positions are reliable, although the supine position with allometric data normalization provided the best results.
Empirical Investigation of Antenna Beamwidth Effects on the ITU-R Building Entry Loss (BEL) Model Based on 32 GHz Measurements

Recently, the ITU-R developed a building entry loss (BEL) propagation model covering millimeter-wave (mmWave) frequency bands, assuming omnidirectional antenna reception. Anticipating the application of directional beamforming (or antennas) employment in mmWave systems, this paper investigates the antenna beam width effects on the BEL based on 32 GHz measurements. We conducted the measurements with three antennas (Omni, 10° horn and 30° horn) at two building sites. These two buildings were specifically selected as candidates in that they followed the ITU - R building classifications of traditional type and thermally-efficient type. In both buildings, the BEL variations with respect to beam angle rotation were observed to be at least 17 dB (up to 50 dB); therefore, precise beam alignment is required. We also observed that the BEL increases as the beamwidth gets narrower, which is due to the fact that the narrower beamwidth antenna captures fewer multipath components while beamforming gain is normalized when calculating the propagation loss.
Performance Estimation of Induction Motor using Artificial Neural Network

This paper presents a performance estimation method of the induction motor (1M) using the artificial neural network (ANN). The ANN is utilized to approximate the performance such as the current, power factor, torque, and efficiency. Due to the learning characteristics of the ANN, the overall performance of IM can be predicted only by the data of a specific section. The proposed method can save a lot of time, effort, and cost since measuring all the driving sections is not necessary. Finally, in order to verify the estimates, the experiments were conducted under equivalent conditions and the estimates were compared with measured values.
Improvements in GeTe-based Phase Change RF Switches

Recent progress in GeTe-based phase-change RF switch technology will be presented. Use of tungsten micro-heat-ers in the inline phase change switch (IPCS) processes has improved device performance and reliability. Finite element simulations of the melt/quench process in GeTe for a thermally activated independent tungsten thin film heating element will be shown. A small (0.33mm × 0.61mm) series-shunt single-pole double-throw (SPDT) switch based on 3rd generation IPCS technology was built and characterized. The SPDT switch exhibited less than 1 dB insertion loss in the DC-65GHz bandwidth. We also report measured data of a wide-band, DC-65GHz, monolithic 4-bit attenuator circuit using IPCS technology.
Mutual liking and meta-perception accuracy

The present study investigated the underlying mechanism yielding a positive correlation between dyad members' mutual liking and meta-accuracy (i.e., dyad members who like each other tend to be accurate in judging how their partner sees them). Two pilot studies were first conducted to confirm the presence of the positive correlation. The main study was conducted to test several possible explanations for the observed positive correlation. In the main study, each participant took part in a series of brief interactions with an unacquainted opposite-sex partner three times. In each interaction, participants rated their liking for the partner, evaluated their impression of the partner on 15 items, and finally inferred the partner's impression of them on the same 15 items. The meta-accuracy was operationally defined as the correlation between the partner's impression and the participant's inference. Neither of the two types of unilateral liking (i.e., participant's liking for the partner nor the partner's liking for the participant) predicted meta-accuracy. However, when both members found the partner likeable (i.e., mutual liking was present), the within-dyad average meta-accuracy tended to be high. The implications of these results for meta-perception research are discussed on the basis of Brunswik's lens model framework. Copyright © 2008 John Wiley & Sons, Ltd.
One-to-one mapping between stimulus and neural state: Memory and classification

Synaptic strength can be seen as probability to propagate impulse, and according to synaptic plasticity, function could exist from propagation activity to synaptic strength. If the function satisfies constraints such as continuity and monotonicity, neural network under external stimulus will always go to fixed point, and there could be one-to-one mapping between external stimulus and synaptic strength at fixed point. In other words, neural network "memorizes" external stimulus in its synapses. A biological classifier is proposed to utilize this mapping.
Erays: Reverse Engineering Ethereum's Opaque Smart Contracts

Interacting with Ethereum smart contracts can have potentially devastating financial consequences. In light of this, several regulatory bodies have called for a need to audit smart contracts for security and correctness guarantees. Unfortunately, auditing smart contracts that do not have readily available source code can be challenging, and there are currently few tools available that aid in this process. Such contracts remain opaque to auditors. To address this, we present Erays, a reverse engineering tool for smart contracts. Erays takes in smart contract from the Ethereum blockchain, and produces high-level pseudocode suitable for manual analysis. We show how Erays can be used to provide insight into several contract properties, such as code complexity and code reuse in the ecosystem. We then leverage Erays to link contracts with no previously available source code to public source code, thus reducing the overall opacity in the ecosystem. Finally, we demonstrate how Erays can be used for reverse-engineering in four case studies: high-value multisignature wallets, arbitrage bots, exchange accounts, and finally, a popular smart-contract game, Cryptokitties. We conclude with a discussion regarding the value of reverse engineering in the smart contract ecosystem, and how Erays can be leveraged to address the challenges that lie ahead.
Teaching a Robot Sign Language using Vision-Based Hand Gesture Recognition

This paper presents a novel vision-based hand gesture recognition (HGR) and training system for a human-like robot hand. We implemented and trained a multiclass-SVM classifier and N-Dimensional DTW (ND-DTW) classifier for static posture recognition and dynamic gesture recognition. Training features were extracted from the raw gestures depth data captured by Leap Motion Controller. The experimental results show that multiclass SVM method has an average 98.25% recognition rates and the shortest run time when compared to k-NN and ANBC. For dynamic gestures, ND-DTW classifier displays a better performance than DHMM with an average 95.5% recognition rate and significantly shorter run time. In conclusion, the combination of SVMs and DTW proves the efficiency and high accuracy in proposed human-robot interaction system.
Out-of-Sight Salt-Water Concentration Sensing Using Chipless- RFID for Pipeline Coating Integrity

In this paper, out of sight microwave concentration sensing is presented to detect salty water ingress in pipeline coatings. Unlike conventional sensors that monitor pipeline corrosion, chipless radio frequency identification (RFID) sensors take a predictive approach by monitoring the environmental conditions at the pipe surface. The proposed sensor is composed of a spiral ring resonator, two tag antennas, and two reader antennas. The integrated system is built on a flexible substrate and is conformally wrapped around the pipe. A two-port measurement is performed at the transceiver and the resonant frequency of the sensor is wirelessly monitored. It is shown that the microwave sensor has potential for monitoring salt water ingress in pipeline coatings.
Coumarin Reduces Virulence and Biofilm Formation in Pseudomonas aeruginosa by Affecting Quorum Sensing, Type III Secretion and C-di-GMP Levels

As one of the major pathogens in wound infections, Pseudomonas aeruginosa produces several virulence factors and forms biofilms; these processes are under the regulation of various quorum sensing (QS) systems. Therefore, QS has been regarded as a promising target to treat P. aeruginosa infections. In the present study, we evaluated the effect of the plant-derived QS inhibitor coumarin on P. aeruginosa biofilms and virulence. Coumarin inhibited QS in the P. aeruginosa QSIS2 biosensor strain, reduced protease and pyocyanin production, and inhibited biofilm formation in microtiter plates in different P. aeruginosa strains. The effects of coumarin in inhibiting biofilm formation in an in vitro wound model and reducing P. aeruginosa virulence in the Lucilia sericata infection model were strain-dependent. Transcriptome analysis revealed that several key genes involved in the las, rhl, Pseudomonas quinolone signal (PQS), and integrated QS (IQS) systems were downregulated in coumarin-treated biofilms of P. aeruginosa PAO1. Coumarin also changed the expression of genes related to type III secretion and cyclic diguanylate (c-di-GMP) metabolism. The cellular c-di-GMP level of P. aeruginosa PAO1 and recent clinical P. aeruginosa strains was significantly reduced by coumarin. These results provide new evidence for the possible application of coumarin as an anti-biofilm and anti-virulence agent against P. aeruginosa in wound infections.
A 3D Compact Wideband 16×16 Butler Matrix for 4G/3G Applications

This paper presents the design and implementation process of a compact wideband $\pmb{16}\mathbf{x}\pmb{16}$ Butler Matrix as a beamforming network for 4G and 3G applications, featuring compact wideband branch-line hybrid couplers, Schiffman phase shifters and a 3D approach of the conventional 16×16 Butler Matrix. The $\pmb{16}\mathbf{x}\pmb{16}$ Butler Matrix operates from 1.65 GHz to 2.17 GHz with insertion losses around $\pmb{-16.5}\mathbf{dB}\pmb{\pm 1.2}\mathbf{dB}$ and maximum phase imbalance of $\pmb{\pm 15^{\circ}}$ for phase difference between output port signals.
Jamming Strategy Optimization for Dual-Channel ALOHA Network with Long Time Delay

The dual-channel ALOHA network with long time delay consisting of many cognitive radio terminals has particular dynamic characteristics. Its total throughput changes with the channel selection of terminals, because two channels have different attraction probabilities under the condition that the total packet arrival rate remains constant. We establish a group of differential equations for each channel's network-adjusted arrival rate, and obtain the function relationship of total throughput with the total arrival rate. The influence of the different allocation ratio about jamming resources on each channel is analyzed under the condition that the jamming resources are kept constant. The optimal allocation ratio of jamming resources is obtained, and the total throughput is minimized for this network. The above theoretic analysis is verified by simulations. It not only puts forward a new way for effective jamming on dual-channel ALOHA network with long time delay, but also provides an important reference for the dynamic characteristics research for such networks.
Influence of Sector Coupling in Future Inner City Low Voltage Grids

This work analyses the influence of photovoltaics, battery electric vehicles and heat pumps, that will be present in future low voltage grids. It focuses on network elements and stability, the resulting changes regarding energy flow, as well as the interdependencies among the technologies. Furthermore, the grid convenience of electrical and heat storages in combination with the technologies above is analyzed to reduce the negative effects on the grid and to improve the self-consumption of energy from photovoltaics.The simulations are based on real data measured in a low voltage grid in the city of Cologne. The grid is supplied from one power station and contains 29 multifamily homes as well as one public building. The grid bears development potential with a maximum transformer load of currently 44% and a maximum grid load of 37%. In the result, PV-storage systems can be combined grid friendly with battery electric vehicles. Heat pumps in contrast cause hard to predict, seasonal differences in the load profile which need intelligent storage management to reduce the negative effects on the grid. PV is not capable of reducing the influence of heat pumps on the grid, due to the seasonal differences in demand and generation of energy.
A Low-loss D-band Chip-to-Waveguide Transition Using Unilateral Fin-line Structure

This paper presents a D-band interconnect realized using unilateral finline structure. The interconnect consists of a microstrip line implemented on a 75μm-thick SiC substrate. The line then couples to a unilateral finline taper that is mounted in the E-plane of a standard WR-6.5 D-band waveguide. The interconnect achieves low insertion loss and covers very wide frequency range. The measured minimum insertion loss is 0.67 dB and the maximum is 2 dB per transition across the entire D-band covering the frequency range 110–170 GHz. The transition does not require any galvanic contacts nor any special processing and can be implemented in any of the commercially available semiconductor technologies. This solution provides low-loss wideband packaging technique that enables millimeter-wave systems assembly using a high-performance simple approach.
Human Activity Recognition by Wearable Sensors : Comparison of different classifiers for real-time applications

In recent years, there is a growing interest in Human Activity Recognition (HAR) systems applied in healthcare. A HAR system is essentially made of a wearable device equipped with a set of sensors (like accelerometers, gyroscopes, magnetometers, heart-rate sensors, etc…) and a classifier able to recognize the activity performed. In this study we focused on the choice of the classifier, since there isn’t a unique and consolidated methodology for HAR. The main aim of the study is to compare the performances of 5 classifiers, based on machine learning. Furthermore, we analyzed advantages and disadvantages of their implementation onto a wearable and realtime HAR system. We acquired magnetic and inertial measurement unit (MIMU) signals from 15 young volunteers. For each subject, we recorded 9 signals from tri-axis accelerometer, gyroscope and magnetometer. All signals were divided in 5s-windows and processed to extract 342 features in time, frequency and time-frequency domains. By means of two feature selection steps (correlation-based and genetic algorithm), we reduced the number of features to 69. These features were used as input for the following 5 classifiers: K-Nearest Neighbor (KNN), Feedforward Neural Network (FNN), Support Vector Machines (SVM), Naïve Bayes (NB), and Decision Tree (DT). Our results showed that all classifiers were able to correctly recognize more than 90% of activities. The best performances were obtained by KNN. Analyzing advantages and disadvantages of each classifier for its implementation by means of a microcontroller the most suitable was DT. In fact, this classifier can be easily implemented, it has low memory and computational requirements, and it allows for a further reduction of the required features.