Miracle-dz/UniFAR-FTUs huggingface dataset:
QCM Sensor Arrays, Electroanalytical Techniques and NIR Spectroscopy Coupled to Multivariate Analysis for Quality Assessment of Food Products, Raw Materials, Ingredients and Foodborne Pathogen Detection: Challenges and Breakthroughs

Quality checks, assessments, and the assurance of food products, raw materials, and food ingredients is critically important to ensure the safeguard of foods of high quality for safety and public health. Nevertheless, quality checks, assessments, and the assurance of food products along distribution and supply chains is impacted by various challenges. For instance, the development of portable, sensitive, low-cost, and robust instrumentation that is capable of real-time, accurate, and sensitive analysis, quality checks, assessments, and the assurance of food products in the field and/or in the production line in a food manufacturing industry is a major technological and analytical challenge. Other significant challenges include analytical method development, method validation strategies, and the non-availability of reference materials and/or standards for emerging food contaminants. The simplicity, portability, non-invasive, non-destructive properties, and low-cost of NIR spectrometers, make them appealing and desirable instruments of choice for rapid quality checks, assessments and assurances of food products, raw materials, and ingredients. This review article surveys literature and examines current challenges and breakthroughs in quality checks and the assessment of a variety of food products, raw materials, and ingredients. Specifically, recent technological innovations and notable advances in quartz crystal microbalances (QCM), electroanalytical techniques, and near infrared (NIR) spectroscopic instrument development in the quality assessment of selected food products, and the analysis of food raw materials and ingredients for foodborne pathogen detection between January 2019 and July 2020 are highlighted. In addition, chemometric approaches and multivariate analyses of spectral data for NIR instrumental calibration and sample analyses for quality assessments and assurances of selected food products and electrochemical methods for foodborne pathogen detection are discussed. Moreover, this review provides insight into the future trajectory of innovative technological developments in QCM, electroanalytical techniques, NIR spectroscopy, and multivariate analyses relating to general applications for the quality assessment of food products.
Timing and Design Issues in Formation Flying Distributed SAR

The paper investigates timing aspects of the design and the operations of a formation flying distributed Synthetic Aperture Radar (SAR). The analyzed system considers a satellite cluster including one transmitter and $N$ receivers flying in formation with a dominant along-track baseline. This realizes a sensor receiving $N$ samples at azimuth-displaced positions for each transmitted pulse, enabling several applications. In fact, besides the possibility to implement single-pass multi-baseline interferometric SAR techniques, the bistatic raw data collected by each receiver can be combined to generate a single higher performance image, e.g. High-Resolution Wide-Swath (HRWS) imaging. The paper investigates the latter topic, proposing dedicated solutions to preserve the imaging performance against the effects of relative orbit dynamics and residual orbit control errors. In details, the factor $N$ can be interpreted as the redundancy, or the maximum number of degrees of freedom of the distributed system when compared to a single-channel monostatic SAR. Such a redundancy can be exploited in different ways pending on the application of suitable signal reconstruction and it represents an important parameter affecting the system timing. In this contest, the manuscript proposes an approach to system timing, satisfying not only ambiguity-related issues but also requirements concerning signal parameters, like SNR and\or Peak-to-Side-Lobe Ratio (PSLR). Finally, the timing considerations are recast in the framework of the overall design of a formation flying SAR.
Magnetic Localization of Wireless Sensors for Internally Illuminated Photoreactors

We propose a method for localizing wireless sensors in internally illuminated photoreactors. The position of the sensor is calculated by evaluating the magnetic field of the transmitter coil. The communication channel between the wireless sensors and an external receiver is implemented through an inductive link because of the promising propagation properties of magnetic fields in water and saltwater whose conductivity is higher compared to freshwater (e.g. the conductivity of seawater is on average 400 times that of freshwater). The on-off keying is therefore used as modulation technique on a carrier frequency of 297 kHz. A special receiver architecture is developed for measuring at one position all three x- y- and z-components of the intermediate frequency magnetic field of the transmitter. The receiver consists of three coils positioned orthogonally to each other. The coil signals are amplified by resonant filters and the position is calculated from the receiver signals using the magnetic dipole field equation. A prototype has been implemented and test-measurements performed in order to get a closer look at the accuracy of the method. In future work the sensors will be powered through a second inductive power link, which is already used for powering an internal wireless illumination system.
Steering Study of Linear Differential Microphone Arrays

Differential microphone arrays (DMAs) can achieve high directivity and frequency-invariant spatial response with small apertures; they also have a great potential to be used in a wide spectrum of applications for high-fidelity sound acquisition. Although many efforts have been made to address the design of linear DMAs (LDMAs), most developed methods so far only work for the situation where the source of interest is incident from the endfire direction. This paper studies the steering problem of differential beamformers with linear microphone arrays. We present new insights into beam steering of LDMAs and propose a series of steerable differential beamformers. The major contributions of this paper are as follows. 1) A series of ideal functions are defined to describe the ideal, target beampatterns of LDMAs. 2) We prove that first-order differential beamformers with linear microphone arrays are not steerable and their mainlobes can only be at the endfire directions. 3) We deduce the fundamental conditions for designing steerable differential beamformers with LDMAs. 4) We develop a method to design steerable beamformers with LDMAs using null constraints. Simulations and experiments validate the properties of the developed method.
Overturning circulation, nutrient limitation, and warming in the Glacial North Pacific

Enhanced overturning circulation in the glacial North Pacific caused warming, nutrient limitation, and lower atmospheric CO2. Although the Pacific Ocean is a major reservoir of heat and CO2, and thus an important component of the global climate system, its circulation under different climatic conditions is poorly understood. Here, we present evidence that during the Last Glacial Maximum (LGM), the North Pacific was better ventilated at intermediate depths and had surface waters with lower nutrients, higher salinity, and warmer temperatures compared to today. Modeling shows that this pattern is well explained by enhanced Pacific meridional overturning circulation (PMOC), which brings warm, salty, and nutrient-poor subtropical waters to high latitudes. Enhanced PMOC at the LGM would have lowered atmospheric CO2—in part through synergy with the Southern Ocean—and supported an equable regional climate, which may have aided human habitability in Beringia, and migration from Asia to North America.
Classification of Partial Discharge Fault Sources on SF₆ Insulated Switchgear Based on Twelve By-Product Gases Random Forest Pattern Recognition

Sulphur hexafluoride (SF6) gas insulated switchgear (GIS) is widely used in electrical power supply system and therefore needs regular preventive maintenance. Prediction and diagnosis analysis of faults in GIS using SF6 gas by-products was introduced previously by using 4 to 8 types of by product gases. As latest development on gas analyser, more by-product gases can be detected and used for condition monitoring of the GIS. The type, number, concentration and chemical stability of by-product gases of SF6 GIS are found to be closely correlated to the type of defect. However, the number of by-product gases used increases, the pattern for faults classification become more complex. Thus, further analysis on increasing number of by product gases using intelligent techniques such as pattern recognition is required. In this article, 12 significant by-products captured due to various sources of partial discharge fault in GIS were used. Random Forest (RF) was selected in this work as a multi-class classification technique. The analyses using RF pattern recognition with eight algorithms based on the presence and concentration of the gas by-products were carried out. The RF algorithm successfully recognises a given defect with an accuracy of 87.5% for all defects fault classification. The performance of the RF algorithm is 1.5 times better than the decision table algorithm which is the next best algorithm. This research illustrates the feasibility and applicability of an effective GIS diagnostic using gas by-products analyses, and in particular, using the RF pattern recognition.
Mobile Antenna Matching Study Considering Different Holding Positions at 2100 MHz Frequency

The purpose of the present research is to study mobile phone Dipole antennas’ matching to a free space with a variety of human hand (fingers) positions in case of different positions of the human head and the headset; Since the hand, holding the mobile phone, absorbs a big part of emitted energy during EMF exposure process and therefore, affects antenna matching conditions, it was great importance to estimate the SAR values in the human head, and to investigate the dependency between SAR and S11 coefficient (antenna matching parameter). The EMF in near and far zones and reradiated power are also studied. Numerical simulation is conducted on realistic nonhomogeneous human head and hand models by the FDTD (Finite Difference Time Domain) Method at 2100 MHz standard frequency.
Event-Driven Distributed Kalman-Consensus Filter with Limited Memory Information

Consider the problem that the estimation accuracy is inversely proportional to the energy consumption in process monitor with wireless sensor networks (WSNs), the concept of the time-efficiency window is proposed based on the relationship between timeliness and information efficiency. And then, an improved event-driven mechanism combined with this time-efficiency window (TEW) is also designed. Consequently, a novel event-driven distributed Kalman-consensus filter with time-efficiency window (TEDKF) is presented. By adjusting the length of the time-efficiency window, the effective historical data stored in each sensor is used to information fusion. And then, the lifetime of WSNs becomes longer on the condition that the similar filtering accuracy is achieved than that of the event-driven distributed Kalman-consensus filter (EDKF). Finally, a simulation example is given to show the effectiveness of the proposed filter.
Repurposed Tocilizumab in Patients with Severe COVID-19

Key Points Tocilizumab could prolong survival among hospitalized patients with severe COVID-19. Tocilizumab weakens the inflammatory response while sustaining immune responses. During the tocilizumab treatment, no severe adverse drug reactions were reported. The coronavirus disease 2019 (COVID-19) has caused a global pandemic, resulting in considerable morbidity and mortality. Tocilizumab, an inhibitor of IL-6, has been widely repurposed as a treatment of severely ill patients without robust evidence supporting its use. In this study, we aimed to systematically describe the effectiveness of treatment and prevention of the cytokine storms in COVID-19 patients with tocilizumab. In this multicentered retrospective and observational cohort study, 65 patients with COVID-19 receiving tocilizumab and 130 not receiving tocilizumab were propensity score matched at a ratio of 2:1 based on age, sex, and comorbidities from January 20, 2020 to March 18, 2020 in Wuhan, China. After adjusting for confounding, the detected risk for in-hospital death was lower in the tocilizumab group versus nontocilizumab group (hazard ratio = 0.47; 95% confidence interval = 0.25–0.90; p = 0.023). Moreover, use of tocilizumab was associated with a lower risk of acute respiratory distress syndrome (odds ratio = 0.23; 95% confidence interval = 0.11–0.45; p < 0.0001). Furthermore, patients had heightened inflammation and more dysregulated immune cells before treatment, which might aggravate disease progression. After tocilizumab administration, abnormally elevated IL-6, C-reactive protein, fibrinogen, and activated partial thromboplastin time decreased. Tocilizumab may be of value in prolonging survival in patients with severe COVID-19, which provided a novel strategy for COVID-19–induced cytokine release syndrome. Our findings could inform bedside decisions until data from randomized, controlled clinical trials become available.
Synthesis of the Induction Motor Control System with Coordinate Observer

Synthesis of the main links and the system as a whole is given. The work of various types of voltage regulators is analyzed and the advantages of the proposed transistor variant are substantiated. The equation of the mechanical characteristic for such control is obtained. The dependences of the critical moment on the magnitude of the control signal and the shunting resistance are given. The equations of the generalized machine are derived, on the basis of which the circuit of the torque calculator is formed. The structure of an asynchronous motor designed for control on the working part of the characteristic under scalar control is considered. On its basis, using the torque calculator, a scheme is created for the observer of the speed of an induction motor. Equations for calculating the links of this scheme are given. Formed feedback signals are used to build the structure of subordinate regulation. Expressions are given for the calculation of regulators and the system as a whole. The simulation of the investigated asynchronous electric drive for various operating modes.
Intrusion Detection based on Non-negative Positive-unlabeled Learning

Due to the diversity of network traffic flow, intrusion detection is usually studied as an anomaly detection problem. In this paper, Positive-unlabeled with Non-negative Risk Estimator(nnPU) learning is introduced for intrusion detection. The cyber attacks is treated as positive samples in PU learning. A risk estimator is raised to estimates the binary classification loss. For data imbalance in intrusion detection, we improve the risk estimator of nnPU through focal loss(FL-nnPU). The dynamic weights in focal loss is used to balance the small class prior. The experiments result show that FL-nnPU have a close performance to binary classification, and it performs better than nnPU under data imbalance problems.
Land Use Classification Using High-Resolution Remote Sensing Images Based on Structural Topic Model

Remote sensing images are primary data sources for land use classification. High spatial resolution images enable more accurate analysis and identification of land cover types. However, a higher spatial resolution also brings new challenges to the existing classification methods. In the low-level feature spaces of remote sensing images, it is difficult to improve classification performance by modifying classifiers. Probabilistic topic models can connect low-level features and high-level semantics of remote sensing images. Latent Dirichlet allocation (LDA) models are representatives of probabilistic topic models. However, at present, probabilistic topic models are mainly adopted for scene classification and image retrieval in remote sensing image analysis only. In this study, multiscale segmentation was employed to construct bag-of-words (BoW) representations of high-resolution images. The segmented patches were then utilized as “image documents. ” A structural topic model was used with an LDA model to import spatial information from the image documents at two levels: topical prevalence and topical content in the form of covariates. In this way, latent topic features in image documents can be more accurately deduced. The proposed method showed more satisfactory classification performance than standard LDA models and demonstrated a certain degree of robustness against the changes in the segmentation scale. Acknowledgement for the data support from “Yangtze River Delta Science Data Center, National Earth System Science Data Center, National Science & Technology Infrastructure of China (http://nnu.geodata.cn:8008)”.
Network Security in Software defined Networks (SDN)

Based on the generalized definition of a network, we know that it is made up of a number of nodes. Sending and receiving of data takes place via these nodes. This process is characterized by the permission provided and requirement of sharing data. Basically, networking helps the nodes across the globe to connect and enable data transfer. Software Defined Networking (SDN) is a smart networking technique. It brings together other disciplines with networking for example, programming, research etc. The SDN model is predominantly controlled by a central unit called controller. All the communication takes place via this controller; however, it has a disadvantage. If the controller anyhow fails or is hacked, the entire system will either fail or get corrupted. In this paper disadvantage of the SDN has overcome with the relevant solution.
Synthetic characteristics of large carbon cluster ions by laser ablation of polymers in vacuum

The synthetic characteristics of large carbon cluster ions by laser ablation of polymers in vacuum were investigated. Time-of-flight mass spectrometry was used for analyzing the masses of ionic species produced by laser ablation. We found that large carbon cluster ions Cn+ with n up to 400 were synthesized in vacuum when copolymer of ethylene and tetrafluoroethylene, polyvinyliden fluoride, and chlorotrifluoroethylene were employed as the target material. Since the synthesis of large cluster ions in vacuum is a surprising phenomenon, we examined the synthesis efficiency in various experimental conditions. By comparing mass spectra obtained from various polymers containing hydrogen and/or halogen atoms, the existence of both hydrogen and halogen atoms in polymers do not directly contribute to enhance the synthesis efficiency of large carbon clusters. In addition, microscopic observations of surface morphologies of laser-ablated polymers revealed that the clustering reactions in eroded craters had little co.
Combined Control System for Structural and Parametric Uncertain Non-Affine Plants with Delay in Control

Under conditions of priori parametric and structural uncertainties and influence of external noise, the synthesis of combined control law for class of non-affine single-channel plants with scalar output in the presence of control delay is considered. To compensate the negative effect of known delay in control the predictor-compensator is connected in parallel with the plant in the system. The synthesis of structure of the combined regulator is based on use of the hyperstability criterion. Estimates of unmeasured state variables are obtained with the help of filter corrector; therefore, the synthesized system is L-dissipative. To confirm the operability of the obtained system and ensure the required quality of its transient processes, it is performed simulation modeling of the synthesized system. The results of simulation showed that the developed system satisfies the required properties and provides the desired quality of the non-affine plant functioning in the presence of control delay and uncontrolled external disturbances.
Contact Force Estimation from Raw Photoplethysmogram Signal

Commercial smartwatches and fitness trackers are integrating increasingly advanced physiological sensors. For optimal performance, such devices need to be firmly coupled to the body, yet also remain comfortable when worn for extended periods of time. Existing solutions for measuring the contact force in order to ensure it is in an optimal tightness range typically depend on direct force measurement, but this adds hardware, and therefore cost, to the devices. This paper presents a novel method for estimating contact force by using only an optical heart rate sensor, as already found in many wearable devices. Initial tests indicate that the proposed method can estimate contact force with a mean absolute error of 0.36N, on par with FSRs. This new approach has the potential to expand the utility of existing sensors for both researchers and end-users, with anticipated applications not only in optimizing physiological sensing, but also in haptic information delivery.
Methods for Comparing Execution Times of Different Input Data when Real-Time Tasks Run on Complex Computer Architectures

Real-time tasks executed on complex computer architectures suffer large interference from other activities executing on the same system, hence generating noise in the observed execution times. In this context, it is difficult or impossible to determine the worst scenario for tasks' measurement-based temporal analysis, i.e., the hardware state and execution path that generates the longest execution time. Both the hardware effects and the execution paths depend directly or indirectly on the input data used. In this work, we (1) performed an empirical assessment of different measurement methods, with the objective of identifying which ones enable comparing different input data with respect to the generation of longer execution times, (2) implemented a genetic algorithm in which the fitness function is based on execution time measurements selected using both traditional and novel methods, showing the relevance of the measurement method for input data analysis. The focus of the work is hence not on finding tasks' worst input data, but on measurement methods that allow reliably comparing tasks' execution times produced using different input data by suppressing complex computer architectures' noise from measurements.
Serum Anti-HPV Antibody Titer as a Marker of Vaccine Effectiveness in Males with Genital Infection

Introduction: Persistent human papillomavirus (HPV) semen infection is increasingly associated with male infertility. Adjuvant HPV vaccination is suggested to reduce the time to clearance and the disease relapse in males with persistent HPV semen infection. However, only a sub-population of patients show a clinical benefit from adjuvant vaccination. Here, we aimed to address the effectiveness rate of HPV adjuvant vaccination in males with genital tract infection and the possible prognostic markers of healing. Methods: Clinical records from 379 patients with persistent seminal HPV detection, all receiving HPV adjuvant vaccination, were considered. Clinical data, including genital HPV-DNA assessment by INNO-LiPA genotyping, semen HPV-DNA analysis by FISH analysis and serum antibody titer, were collected at basal (T0) and after 6 months (T1) since the vaccination cycle ended. Results: Clearance of genital HPV-DNA was recorded in 326 (86%) patients. Serum HPV-antibody titer at T1 was the most important prognostic factor associated with HPV-DNA clearance. A serum antibody titer equal to or greater than the threshold value 1:125, obtained by ROC curve analysis, was prognostic of healing. Conclusions: Anti-HPV antibody represents a suitable marker of adequate immune response to HPV vaccination in patients with genital infection.