Miracle-dz/UniFAR-FTUs huggingface dataset:
Co-Channel Interference Suppression for LTE Passive Radar Based on Spatial Feature Cognition

Passive radars based on long-term evolution (LTE) signals suffer from sever interferences. The interferences are not only from the base station used as the illuminator of opportunity (BS-IoO), but also from the other co-channel base stations (CCBS) working at the same frequency with the BS-IoO. Because the reference signals of the co-channel interferences are difficult to obtain, cancellation performance degrades seriously when traditional interference suppression methods are applied in LTE-based passive radar. This paper proposes a cascaded cancellation method based on the spatial spectrum cognition of interference. It consists of several cancellation loops. In each loop, the spatial spectrum of strong interferences is first recognized by using the cyclostationary characteristic of LTE signal and the compressed sensing technique. A clean reference signal of each interference is then reconstructed according to the spatial spectrum previously obtained. With the reference signal, the interferences are cancelled. At the end of each loop, the energy of the interference residual is estimated. If the interference residual is still strong, then the cancellation loop continues; otherwise it terminates. The proposed method can get good cancellation performance with a small-sized antenna array. Theoretical and simulation results demonstrate the effectiveness of the proposed method.
A unifying perspective of the ultrafast photo-dynamics of Orange Carotenoid Protein from Synechocystis: peril of high-power excitation, existence of different S* states and influence of tagging

A substantial number of Orange Carotenoid Protein (OCP) studies have aimed to describe the evolution of singlet excited states leading to the formation of photo-activated form, OCPR. The most recent one suggests that three picosecond-lived excited states are formed after the sub-100 fs decay of the initial S2 state. The S* state which has the longest reported lifetime of a few to tens of picoseconds is considered to be the precursor of the first red photoproduct P1. Here, we report the ultrafast photo-dynamics of the OCP from Synechocystis PCC 6803, carried out using Visible-NIR femtosecond time-resolved absorption spectroscopy as a function of the excitation pulse power and wavelength. We found that a carotenoid radical cation can form even at relatively low excitation power, obscuring the determination of photo-activation yields for P1. Moreover, the comparison of green (540 nm) and blue (470 nm) excitations revealed the existence of an hitherto uncharacterized excited state, denoted as S∼, living a few tens of picoseconds and formed only upon 470 nm excitation. Since neither the P1 quantum yield nor the photo-activation speed over hundreds of seconds vary under green and blue continuous irradiation, this S∼ species is unlikely to be involved in the photo-activation mechanism leading to OCPR. We also addressed the effect of His-tagging at the N- or C-termini on excited state photo-physical properties. Differences in spectral signatures and lifetimes of the different excited states were observed, at variance with the usual assumption that His-tagging hardly influences protein dynamics and function. Altogether our results advocate for careful consideration of the excitation power and His-tag position when comparing the photo-activation of different OCP variants, and beg to revisit the notion that S* is the precursor of photoactivated OCPR. TOC
A simple technique to evaluate winding losses including two-dimensional edge effects

This paper presents a simple technique for evaluating the AC losses of magnetic windings including two-dimensional (2-D) edge effects. Although one-dimensional (1-D) analysis tools have been developed to evaluate winding losses in conductor windings, the additional AC losses due to 2-D edge effects are quite significant and cannot be predicted by the developed 1-D solutions. The proposed approach is based on introducing a set of correction factors for the 1-D analysis results to account for the 2-D edge effects. Finite-element analyses are utilized to validate the obtained results.
Contacts Detection in PCB Image by Thinning, Clustering and Flood-filling

The known K-means clustering, flood-fill and thinning algorithms are used to find coordinates of contacts in PCB images. Images of different types and colors are considered. The clustering algorithm is used to reduce a number of colors, to get uniform colors and to separate objects of the PCB image: background, traces, inscription and contacts. The thinning algorithm is used to build skeletons and to find specific points indicating pixels of contacts. The flood-fill algorithm is used to mark contacts, traces, background and inscriptions. Contacts with and without holes are considered.
Stationary planar-surface target detection in an unknown indoor environment

It is difficult to detect a stationary object in practice, especially in an unknown indoor environment, because (a) there is no distinct speed difference between the targets and the background; (b) responses of the targets are contaminated by dense unknown clutter; (c) a priori knowledge of the background is not always available for some scenarios. In this paper, a set of ultra-wideband sensors are used to detect a stationary target with a planar diffuse surface. It is shown that, the relative spectrum-shifts of the data after data-projection operation, are closely connected to the illumination-angle differences. Based on this, a detector is designed, and the location and the orientation of the target are determined. In order to mitigate the influence of clutters, a “time-shift & accumulation” scheme is designed to enhance the signal. As a consequence, the signal-to-interference-and-noise ratio is increased. In addition, results from measurement in a realistic indoor environment are provided.
Gate drive considerations for IGBT modules

The switching performance of an insulated gate bipolar transistor (IGBT) module depends on the drive circuit characteristics and external DC loop inductance. The authors discuss the influence of these parameters on switching losses, diode recovery, switching voltage transients, short-circuit operation, and d nu /dt induced current. The present work is tutorial and identifies trends. It is intended to help the circuit designer to apply the IGBT module to best advantage. <<ETX>>
Power gain in feedback amplifiers, a classic revisited

A tutorial review of a classic paper by Samuel J. Mason (1954) is described. That paper contained the first definition of a unilateral power gain for a linear two-port and the first proof that this grain is invariant with respect to linear lossless reciprocal four-port embeddings, thereby making it useful as a figure of merit intrinsic to the device. In this work, that original paper is brought up to date, a tutorial exposition of its contents is presented in a modern form, and its significance and applications in microwave engineering are discussed. The subsequent advances in the subject area are summarized, so that the original paper can be placed within a broader context and understood with a more general perspective. >
Accelerometer based gyro-free multi-sensor generic inertial device for automotive applications

The importance of developing a unified inexpensive generic inertial device is substantiated in this paper based on the current situation in the automotive market. A gyro-free architecture of the generic inertial device is proposed as a solution. Exclusion of gyroscopes from the inertial system allows one to achieve an essential decrease in price, while the inertial system based on multiple accelerometers distributed inside the vehicle can still deliver data at sufficient accuracy for automotive inertially-aided systems. The paper also focuses on the choice of mathematical models as a Harwich of models evolving from the basic six sensor gyro free model, and shows the importance of optimization of parts of the design that permit formalization but involve tedious work. The original approach to the choice of optimal sequence of elementary operations is then described.
The Study on the Nanocutting by Rigid Body Tool at the Gas Environment Using Molecular Dynamics Simulations

This study successfully simulated the single crystal copper nanocutting with a rigid body tool at the nitrogen gas environment using molecular dynamics, and analyzed the workpiece stress distribution and dislocation during nanocutting. After simulations, a diamond rigid tool with a completely sharp produce a shear plane during cutting. The distribution of equivalent stress was greatest at the shear zone and that residual stress occurred on the machined surface. And the stress gets smaller as the distance from the chip surface is farther.
Gender Difference in the Associations among Heavy Metals with Red Blood Cell Hemogram

This study aimed to investigate gender differences in the association between heavy metals and hemograms including hemoglobin (Hgb), mean corpuscular volume (MCV) and mean corpuscular hemoglobin concentration (MCHC). A health survey of 2447 participants was conducted in southern Taiwan between June 2016 and September 2018. Seven heavy metals were measured: blood lead (Pb), urine nickel (Ni), urine chromium (Cr), urine manganese, urine arsenic (As), urine copper and urine cadmium (Cd). The results show that in females, Pb and Ni were significantly negatively associated with Hgb. In addition, As and Cd were significantly positively, and Pb and Ni were significantly negatively, associated with MCV, in males and females, respectively. The interactions between gender and Ni and gender and Cd in MCV were statistically significant. Further, Pb, in males, and Pb, Ni and Cr, in females, were significantly negatively associated with MCHC. In conclusion, in females, associations of red blood cell (RBC) hemograms with heavy metals such as Pb and Ni were found. In males, heavy metals such as Pb, As and Cd were found to associate with RBC hemograms. Further research is warranted to discuss the mechanism behind these associations.
Effect of biochar blended organic fertilizers on soil fertility, radish productivity and farm income in Nepal

Declining soil fertility and nutrient availability are one of the major threats to reducing crop productivity in Nepal. A field experiment was conducted to assess the potential of biochar (10 t ha-1) blended with organic and inorganic fertilizers on improving soil fertility and radish productivity in Morang district, Nepal. Biochar was prepared from locally available twigs, branches, and wood using the soil pit “Kon tiki” method. The experiment was laid out in Randomized Complete Block Design with 7 treatments having four replications viz., control (CK), biochar (BC), biochar + cattle manure (CM), biochar + poultry manure (PM), biochar + cattle urine (CU), biochar + commercial biofertilizers (BF) and biochar + inorganic fertilizers (urea-N). The nitrogen rate used in all the treatments was equivalent to 100 kg ha-1. The agronomic effect of biochar blended organic amendments was compared with control and inorganic urea-N treatments. Biochar amended plots showed significantly higher soil pH (6.5), organic matter (4%), total N% (0.8%), available P (80.1 kg ha-1), and K (203.6 kg ha-1) compared with control. CM increased marketable yield by 320% (63 t ha-1) and biomass yield by 198% (100 t ha-1) compared with control (15.0 t ha-1 and 34 t ha-1) of marketable and biomass yield, respectively. CM increased marketable yield by 44% compared with the urea-N treatment (44 t ha-1). Moreover, net return was observed highest with CM treatment among all the organic and urea-N treatments. The study suggests that the combination of biochar with locally produced cattle manure has the potential to increase radish productivity and could compete with mineral nitrogen fertilizers while producing similar or even higher crop yields and economic returns.
Control of Position and Pose on Virtual Axis Polishing Process

To guarantee the effect of virtual axis machine tool, improve processing quality, research on analyze machining parameter optimization problem on affect the machining accuracy of the virtual axis machine tool, position and pose of the virtual axis machine tool are analyzed, and find out the key factors that affect the position and pose, and progress the actual processing experiment of position and pose for the optimized processing parameters, the results of actual processing proves that the optimized processing parameters can guarantee good processing effect.
Practical recommendations on double score matching for estimating causal effects

Unlike in randomized clinical trials (RCTs), confounding control is critical for estimating the causal effects from observational studies due to the lack of treatment randomization. Under the unconfoundedness assumption, matching methods are popular because they can be used to emulate an RCT that is hidden in the observational study. To ensure the key assumption hold, the effort is often made to collect a large number of possible confounders, rendering dimension reduction imperative in matching. Three matching schemes based on the propensity score (PSM), prognostic score (PGM), and double score (DSM, ie, the collection of the first two scores) have been proposed in the literature. However, a comprehensive comparison is lacking among the three matching schemes and has not made inroads into the best practices including variable selection, choice of caliper, and replacement. In this article, we explore the statistical and numerical properties of PSM, PGM, and DSM via extensive simulations. Our study supports that DSM performs favorably with, if not better than, the two single score matching in terms of bias and variance. In particular, DSM is doubly robust in the sense that the matching estimator is consistent requiring either the propensity score model or the prognostic score model is correctly specified. Variable selection on the propensity score model and matching with replacement is suggested for DSM, and we illustrate the recommendations with comprehensive simulation studies. An R package is available at https://github.com/Yunshu7/dsmatch.
Static and Dynamic Analysis of Multi-Story Buildings, Including P-Delta Effects

The P-Delta phenomenon is an area of concern to structural engineers. Traditional methods for incorporating P-Delta effects in analysis are based on iterative techniques. These techniques are time-consuming and are in general used for static analysis only. For building structures, the mass, which causes the P-Delta effect, is constant irrespective of the lateral loads and displacements. This information is used to linearize the P-Delta effect for buildings and solve the problem “exactly”, satisfying equilibrium in the deformed position, without iterations. An algorithm is developed that incorporates the P-Delta effects into the basic formulation of the structural stiffness matrix as a geometric stiffness correction. This procedure can be used for both static and dynamic analysis and will account for the lengthening of the structural time periods and changes in mode shapes due to P-Delta effects. The algorithm can be directly incorporated into building analysis programs.
HPCFAIR: Enabling FAIR AI for HPC Applications

Artificial Intelligence (AI) is being adopted in different domains at an unprecedented scale. A significant interest in the scientific community also involves leveraging machine learning (ML) to effectively run high performance computing applications at scale. Given multiple efforts in this arena, there are often duplicated efforts when existing rich data sets and ML models could be leveraged instead. The primary challenge is a lack of an ecosystem to reuse and reproduce the models and datasets. In this work, we propose HPCFAIR, a modular, extensible framework to enable AI models to be Findable, Accessible, Interoperable and Reproducible (FAIR). It enables users with a structured approach to search, load, save and reuse the models in their codes. We present the design, implementation of our framework and highlight how it can be seamlessly integrated to ML-driven applications for high performance computing applications and scientific machine learning workloads.
Building perspective awareness as a workplace practice

Purpose The present study aims to describe the implementation of a facilitated dialogue model intended to improve communication across professional logics and knowledge boundaries in two units of a large health-care organization in Sweden. Design/methodology/approach This is a mixed-methods study with interviews, field observations and follow- up questionnaires that were conducted during the implementation process. Findings The conclusion drawn in this study is that it is possible to change and improve the dialogue between health-care professionals with the help of a tailored, facilitated dialogue model. The authors found that different professional logics can indeed meet and share perspectives if the right conditions are provided. Moreover, an improved dialogue between different professional groups may contribute to work satisfaction, engagement, social cohesion and communication between professionals. Practical implications This study shows that the right organizational conditions, such as support from managers, must exist if the model’s inherent possibilities are to be used. Inhouse facilitation may be a sustainable model for facilitated workplace dialogue when its implementation is supported by the overall organization. Originality/value The contribution is an empirically based analysis of a new form of model for mediating perspectives within an organization with distinct professional roles. This study shows how, under the right conditions, the model can contribute to a perspective awareness and thus a more mature work organization.
Analysis of Factors Affecting Indonesian Coffee Exports in 2001-2018 Using The Vector Autoregression (VAR) Approach

Coffee exports are influenced by the exchange rate, the price of coffee and the amount of production. The purpose of the study was to determine the short-term and long-term relationship between coffee exports in 2001-2018. The research method is quantitative descriptive using classical assumption test and Error Correlation Model (ECM). The results of the VAR study are that coffee exports are not affected by coffee prices, coffee production and the rupiah exchange rate. Coffee exports were not significantly affected by coffee production, coffee prices and the exchange rate (exchange rate) using VAR. result Grangger's is that coffee production affects coffee exports and the exchange rate affects coffee exports. Test IRF and VD is the coffee production is influenced by coffee prices and the exchange rate, the price of coffee affects the production of coffee, coffee exports and the exchange rate and the exchange rate is influenced by the price of coffee and coffee exports. As for advice because coffee production affects coffee exports from Indonesia then, the government should do a vertical integration from upstream (people's plantations) to downstream (industries) to increase export expansion.
Aqueous extracts from Acalypha gaumeri and Bonellia flammea for leaf blight control in chrysanthemum (Chrysanthemum morifolium)

The chrysanthemum is the second most important cut flower in the world, however, its quality and commercial value is affected by the leaf blight produced by Alternaria spp. The objective of this work was to evaluate the causal agent of leaf blight in Chrysanthemum, and its control with aqueous extracts of Acalypha gaumeri and Bonellia flammea. The fungus was collected and identified from leaves and stems of chrysanthemum plants. Subsequently, molecular identification and pathogenicity tests were performed on chrysanthemum plants. In the field, treatments were evaluated with weekly applications of: T1: B. flammea bark extract, T2: A. gaumeri root extract, T3: negative control (water) and T4: Captan® fungicide. Prior to the application of the treatments, plants were inoculated with the isolated fungus (2.5 × 106 spores mL-1) and severity was evaluated. Alternaria chrysanthemi was identified as the causal agent. Based on the severity percentage, the lowest averages of the area under the disease progress curve, the lowest rates of apparent infection, the lowest intensity of the disease and the greater effectiveness in controlling the disease were observed for T2 (165, 0.017, 8 and 67%, respectively) followed by T1 (186, 0.022, 13 y 50 %, respectively) and T4 (179, 0.023, 14 y 45%, respectively), observing a significantly different than negative control T3 (369, 0.025, 25 and 0%, respectively). Plant extracts have potential to be used as an alternative in the management of Alternaria leaf blight in chrysanthemum.
Understanding the therapeutic factors of the main psychological treatment stage in a residential treatment setting: a qualitative approach

ABSTRACT The purpose of this article is to understand deeply the important elements of the middle phase of recovery. The participants were 14 people suffering from addiction to drugs, who met the criteria for substance use disorder according to the DSM-V. The data obtained by semi-structured interview were qualitatively analyzed by interpretive phenomenological analysis. The results deepen the importance of the groups through the highlighting of the important quality characteristics, the difficulties and the positive aspects of the treatment process, the relationships that develop, the deeper causes of the addiction, the mainly negative emotions that prevail in this phase and the anxieties. for the next stage. The results are discussed on the basis of the enhancement of the therapeutic interventions that are followed at this middle recovery stage.
A Fog-Based Architecture for Latency-Sensitive Monitoring Applications in Industrial Internet of Things

In industrial wireless sensors networks (IWSNs) deployments, data management and processing tasks are often delegated to centralized computing facilities. Albeit providing an abundance of resources, these solutions impose several drawbacks, stemming from the higher latency they may introduce, as well as from security/privacy issues. To deal with these shortcomings, in this article, we propose an architecture designed for industrial monitoring duties, based on the Fog computing paradigm. In particular, we devised a Fog layer to host a data aggregation algorithm based on singular value decomposition (SVD). Considering a real-world case study about a distributed monitoring system for industrial motors, the benefits of the proposed solution in terms of network performances, i.e., latency and packet delivery ratio, are analyzed using the OMNET++ simulator. Besides, the system implements a set of security mechanisms at different levels (i.e., IWSN, Fog, and Cloud). In particular, we propose a new lightweight and energy-efficient ciphering algorithm for resource-constrained industrial motes. According to our experiments, the new algorithm reduces energy consumption by a factor of three compared to Advanced Encryption Standard-128.