Miracle-dz/UniFAR-FTUs huggingface dataset:
Cognitive Radar Waveform Design Based on Multi-objective Optimization Criteria

In electronic warfare, the target is usually in a complex jamming environment. Cognitive waveform design is very important as an active and intelligent anti-jamming method. It is usually performed in the frequency domain and based on a single criterion, which is difficult to take into account the detection and anti-jamming performance and the operation is complex. Aiming at above problems, in the case of corner reflector jamming, a cognitive waveform design method based on multi-objective optimization criteria is proposed. We construct a multi-objective optimization model based on the maximum signal-to-jamming ratio (SJR), the minimum time delay resolution constant (TRC) and the minimum peak sidelobe ratio (PSLR). Then, it is converted into a single-objective function by the weighting method and solved by the particle swarm optimization (PSO) algorithm. The simulation results show that the method improves the signal-to-jamming ratio and range resolution of radar echoes and effectively enhances the ability of target detection and anti-jamming.
Experiments on the lift and drag of spheres suspended in a Poiseuille flow

An experimental investigation of the fluid dynamic forces on spheres suspended in a Poiseuille flow was performed. Small spheres of polystyrene, nylon, and Lucite, having diameters ranging from 0.061 in. to 0.126 in. were suspended in Poiseuille flows in a 0.419 in. diameter tube. Variations in particle size and density, the fluid properties, and the angle of inclination of the tube, resulted in a sphere Reynolds number (based on particle diameter and approach velocity) ranging from 80 to 250. The results are presented as curves which include the coefficients of lift and drag, and the dimensionless rotation speed plotted versus Reynolds number and a dimensionless shear parameter.
Improving Catalytic Activity of “Janus” MoSSe Based on Surface Interface Regulation

The monolayer Janus MoSSe is considered to be a promising catalytic material due to its unique asymmetric structure. In order to improve its catalytic performance for hydrogen evolution reactions (HERs) and oxygen evolution reactions (OERs), many attempts have been made. In this work, a series of transition metal (TM) atoms were anchored on the Janus MoSSe surface to screen effective TM single-atom catalysts for HERs and OERs through density functional theory (DFT) calculations. Fe@MoSSe presents excellent HERs performance and Ni@MoSSe presents excellent catalytic performance for OERs with extremely low over-potential of 0.32 V. The enhanced activity is attributed to the modest energy level of the d band center of the transition metal atom, and the transition metal atom improves the conductivity of the original MoSSe and offers unoccupied states near the Fermi level. At the same time, the anchoring of transition metal atoms redistributes the charge in the MoSSe system, which effectively regulates the electronic structure of the material itself. The strain calculation shows that the activity of the catalyst can be improved by reasonably adjusting the value of the applied strain.
Static and dynamic dipole polarizability of cylindrically confined hydrogen atom

The non-relativistic static and dynamic dipole polarizabilities of hydrogen atom experiencing a cylindrical confinement are investigated. Two methods based on B-Splines are used for the computations of the energies and wavefunctions. The first method is a variational based method while the second one proceeds by a fit of the non-separable Coulomb potential in the product form. The computed energies compare very well with previous computations. They converge, as well as the dipole polarizability, to the exact unconfined free atom values. The fit approach is found to be advantageous, as it helps saving the computational time without a loss of accuracy. Dynamic polarizabilities have been reported for various dimensions of the confining cylinder.
A 60-GHz Hybrid FMCW-Doppler Radar for Vibration Detection With a Robust I/Q Calibration Method

In the field of noncontact sensing, both the continuous-wave (CW) Doppler radar and the frequency-modulated CW (FMCW) radar have their own superiorities. A combination of these two radar modes would be a suitable choice to accommodate various application scenarios. This article presents a 60-GHz hybrid FMCW-Doppler radar transceiver fabricated in a 65-nm CMOS process. An on-chip frequency quadrupler driven by a 15-GHz external signal source is utilized for the 60-GHz hybrid waveform generation. Based on the hybrid operating modes, a robust I/Q imbalance calibration method is also proposed. Specifically, in the Doppler radar mode, the imbalance factors are extracted by evaluating the quadrature beat signals during the FMCW period, and then the interferometry signals are calibrated to improve the detection performance. Unlike the trajectory-based ellipse-fitting method, the accuracy of the estimated imbalance factor is independent of the target displacement. Compared with the test-signal-based imbalance factors extraction ahead of the target detection, the real-time extraction during the target detection is more efficient and can also mitigate the estimation errors caused by environmental variations. With the proposed hybrid radar system and the I/Q calibration method, an 80-mm linear displacement is recovered with a 0.016-mm root mean square error (RMSE), and a periodic vibration with a 1- $\mu \text{m}$ amplitude is detected with a 16.4-dB signal-to-noise ratio (SNR). Multiple-target detection is also performed in the FMCW radar mode, and the vibration trajectories are recovered accurately.
Spin-dependent tunneling through a symmetric semiconductor barrier

The problem of electron tunneling through a symmetric semiconductor barrier based on zinc-blende-structure material is studied. The k3 Dresselhaus terms in the effective Hamiltonian of bulk semiconductor of the barrier are shown to result in a dependence of the tunneling transmission on the spin orientation. The difference of the transmission probabilities for opposite spin orientations can achieve several percents for the reasonable width of the barriers.
The Alexander module, Seifert forms, and categorification

We show that bordered Floer homology provides a categorification of a topological quantum field theory (TQFT) described by Donaldson [Proceedings of the Kirbyfest, Berkeley, CA, 1998, Geometry & Topology Monographs 2 (Geometry & Topology Publications, Coventry, 1999) 87–102]. This, in turn, leads to a proof that both the Alexander module of a knot and the Seifert form are completely determined by Heegaard Floer theory.
Cellular Automaton Approach to Pedestrian Dynamics - Applications

We present applications of a cellular automaton approach to pedestrian dynamics introduced in [1,2]. It is shown that the model is able to reproduce collective effects and self-organization phenomena encountered in pedestrian traffic, e.g. lane formation in counterflow through a large corridor and oscillations at doors. Furthermore we present simple examples where the model is applied to the simulation of evacuation processes.
Gene Expression Analyses of Mutant Flammulina velutipes (Enokitake Mushroom) with Clogging Phenomenon

Abstract Regulation of proper gene expression is important for cellular and organismal survival, maintenance, and growth. Abnormal gene expression, even for a single critical gene, can thwart cellular integrity and normal physiology to cause diseases, aging, and death. Therefore, gene expression profiling serves as a powerful tool to understand the pathology of diseases and to cure them. In this study, the difference in gene expression in Flammulina velutipes was compared between the wild type (WT) mushroom and the mutant one with clogging phenomenon. Differentially expressed transcripts were screened to identify the candidate genes responsible for the mutant phenotype using the DNA microarray analysis. A total of 88 genes including 60 upregulated and 28 downregulated genes were validated using the real-time quantitative PCR analysis. In addition, proteomic differences between the WT and mutant mushroom were analyzed using two–dimensional gel electrophoresis and matrix-assisted laser desorption/ionization-time of flight (MALDI-TOF). Interestingly, the genes identified by these genomic and proteomic analyses were involved in stress response, translation, and energy/sugar metabolism, including HSP70, elongation factor 2, and pyruvate kinase. Together, our data suggest that the aberrant expression of these genes attributes to the mutant clogging phenotype. We propose that these genes can be targeted to foster normal growth in F. velutipes.
A Case Report of Anaphylactic Shock Due to Hornet Sting with Multiple Organ Dysfunction Complications

BACKGROUND: Hornet venom has been recognized to induce lethal systemic effects such as anaphylaxis shock, bronchospasm, acute kidney or liver injury, disseminated intravascular coagulation (DIC), cardiovascular collapse, and even death. It consists of several enzymes and polypeptides with low molecular weights. It has been reported to contain the enzymes phospholipase A2, hyaluronidase, phosphomonoesterase acid ester, α-D-glucosidase, lysophospholipase, α-galactosidase, α-acetylamino-deoxsiglucosidase, and arylamidase. The venom will cause localized or systemic inflammation, an anticoagulant effect that may be fatal. CASE REPORT: Herewith, a survival case report suffered from DIC with multi-organ failure following severe anaphylaxis shock post a hundred or massive Hornet sting. CONCLUSION: We have reported a case of anaphylactic shock after a massive hornet sting with DIC that presented symptoms of shock, AKI, ALI, and multi-site bleeding. Although the mortality rate for similar cases is quite high, the outcome will be better with comprehensive and adequate treatment.
Prolongation of Fate of Bacteriophages In Vivo by Polylactic-Co-Glycolic-Acid/Alginate-Composite Encapsulation

With concern growing over antibiotics resistance, the use of bacteriophages to combat resistant bacteria has been suggested as an alternative strategy with which to enable the selective control of targeted pathogens. One major challenge that restrains the therapeutic application of bacteriophages as antibacterial agents is their short lifespan, which limits their antibacterial effect in vivo. Here, we developed a polylactic-co-glycolic acid (PLGA)/alginate-composite microsphere for increasing the lifespan of bacteriophages in vivo. The alginate matrix in PLGA microspheres encapsulated the bacteriophages and protected them against destabilization by an organic solvent. Encapsulated bacteriophages were detected in the tissue for 28 days post-administration, while the bacteriophages administered without advanced encapsulation survived in vivo for only 3–5 days. The bacteriophages with extended fate showed prophylaxis against the bacterial pathogens for 28 days post-administration. This enhanced prophylaxis is presumed to have originated from the diminished immune response against these encapsulated bacteriophages because of their controlled release. Collectively, composite encapsulation has prophylactic potential against bacterial pathogens that threaten food safety and public health.
Are the Bacteria and Their Metabolites Contributing for Gut Inflammation on GSD-Ia Patients?

Recently, patients with glycogen storage disease (GSD) have been described as having gut dysbiosis, lower fecal pH, and an imbalance in SCFAs due to an increase in acetate and propionate levels. Here, we report the fecal measurement of bacterial-related metabolites formic, acetic, lactic, propionic, and succinic acid, a key metabolite of both host and microbiota, on a previously described cohort of 24 patients (GSD Ia = 15, GSD Ib = 5, 1 GSD III = 1 and GSD IX = 3) and 16 healthy controls, with similar sex and age, using the high-performance liquid chromatography technique. The succinic acid levels were higher in the GSD patients than in the controls (patients = 38.02; controls = 27.53; p = 0.045), without differences between the groups for other metabolites. Fecal pH present inverse correlation with lactic acid (R = −0.54; p = 0.0085), while OTUs were inversely correlated with both lactic (R = −0.46; p = 0.026) and formic (R = −0.54; p = 0.026) acids. Using two distinct metrics of diversity, borderline significance was obtained for propionic acid, affecting the microbial structure on Euclidean basis in 8% (r2 = 0.081; p = 0.079), and for lactic acid, affecting 6% of microbial structure using Bray–Curtis distance (r2 = 0.065; p = 0.060). No correlation was found between SCFAs and total carbohydrate consumption among the participants or uncooked cornstarch consumption among the patients.
Spline petrov-galerkin methods with quadrature

This paper studies certain discrete schemes for mth-order linear 2-point boundary value problems and related eigenvalue problems. The method is a discrete Petrov-Galerkin method, with a trial space of smoothest splines of order m + 2, and a test space of continuous piecewise-linear functions. The method, which extends and generalies recent results of Sloan, Tran and Fairweather for the case m = 2, places no restrictions on the mesh. Under appropriate smoothness assumptions, the order of convergence of the mth derivatives of the boundaryvalue problem is O(h2 max), while that of the (m − 2)th and lower derivatives is O(h4 max). Order O(h4 max) superccnvergence is proved for (m − 1)th derivatives at the breakpoints, and also for the eigenvaiues in the case of the eigenvalue problem
Tree-Based Classifier Ensembles for PE Malware Analysis: A Performance Revisit

Given their escalating number and variety, combating malware is becoming increasingly strenuous. Machine learning techniques are often used in the literature to automatically discover the models and patterns behind such challenges and create solutions that can maintain the rapid pace at which malware evolves. This article compares various tree-based ensemble learning methods that have been proposed in the analysis of PE malware. A tree-based ensemble is an unconventional learning paradigm that constructs and combines a collection of base learners (e.g., decision trees), as opposed to the conventional learning paradigm, which aims to construct individual learners from training data. Several tree-based ensemble techniques, such as random forest, XGBoost, CatBoost, GBM, and LightGBM, are taken into consideration and are appraised using different performance measures, such as accuracy, MCC, precision, recall, AUC, and F1. In addition, the experiment includes many public datasets, such as BODMAS, Kaggle, and CIC-MalMem-2022, to demonstrate the generalizability of the classifiers in a variety of contexts. Based on the test findings, all tree-based ensembles performed well, and performance differences between algorithms are not statistically significant, particularly when their respective hyperparameters are appropriately configured. The proposed tree-based ensemble techniques also outperformed other, similar PE malware detectors that have been published in recent years.
The Construction and Properties of Ellipsoidal Probability Density Functions

[enter Abstract Body]A recipe for the construction of a multivariate probability density function from a normalized symmetric univariate function using a distance metric methodology is developed. A method to perform multivariate integration in a polar coordinate system in an arbitary number of dimensions is described. This method is then used to compute a constant that normalizes the multivariate p.d. f. constructed using the recipe specified here. The use of the Kolmogorov test, as applied to the univariate distribution of the square of the metric distance, for distributional identification is described. A summary of the general properties of the constructed p.d. f. is given including the computation of: the principal moments; Mardia's multivariate kurtosis measure; and, the characteristic and moment generatic functions. Some elements of maximum likelihood estimation are explored.
Influence of DNA-Polymorphisms in Selected Circadian Clock Genes on Clock Gene Expression in Subjects from the General Population and Their Association with Sleep Duration

Background and Objectives: Circadian rhythms have an important implication in numerous physiological and metabolic processes, including the sleep/wake cycle. Inter-individual differences in factors associated with circadian system may be due to gene differences in gene expression. Although several studies have analyzed the association between DNA polymorphisms and circadian variables, the influence on gene expression has been poorly analyzed. Our goal was to analyze the association of genetic variations in the clock genes and the gene expression level. Materials and Methods: We carried out a cross-sectional study of 102 adults (50.9% women). RNA and DNA were isolated from blood and single-nucleotide polymorphisms (SNPs), and the main circadian clock genes were determined. Gene expression of CLOCK, PER1, and VRK2 genes was measured by Reverse-transcription polymerase chain reaction (RT-PCR). The association between the DNA-SNPs and gene expression was analyzed at the gene level. In addition, a polygenic risk score (PRS), including all the significant SNPs related to gene expression, was created for each gene. Multivariable model analysis was performed. Results: Sex-specific differences were detected in PER1 expression, with these being higher in women (p = 0.034). No significant differences were detected in clock genes expression and lifestyle variables. We observed a significant association between the ARNTL-rs7924734, ARNTL-rs10832027, VRK2- rs2678902 SNPs, and CLOCK gene expression; the PER3-rs228642 and PER3-rs10127838 were related to PER1 expression, and the ARNTL-rs10832027, ARNTL-rs11022778, and MNTR1B-rs10830963 were associated with VRK2 gene expression (p < 0.05). The specific PRS created was significantly associated with each of the gene expressions analyzed (p < 0.001). Finally, sleep duration was associated with PER3-rs238666 (p = 0.008) and CLOCK-rs4580704 (p = 0.023). Conclusion: We detected significant associations between DNA-SNPs in the clock genes and their gene expression level in leukocytes and observed some differences in gene expression per sex. Moreover, we reported for the first time an association between clock gene polymorphisms and CLOCK, PER1, and VRK2 gene expression. These findings need further investigation.
The Influence of Forward Osmosis Module Configuration on Nutrients Removal and Microalgae Harvesting in Osmotic Photobioreactor

Microalgae have attracted great interest recently due to their potential for nutrients removal from wastewater, renewable biodiesel production and bioactive compounds extraction. However, one major challenge in microalgal bioremediation and the algal biofuel process is the high energy cost of separating microalgae from water. Our previous studies demonstrated that forward osmosis (FO) is a promising technology for microalgae harvesting and dewatering due to its low energy consumption and easy fouling control. In the present study, two FO module configurations (side-stream and submerged) were integrated with microalgae (C. vulgaris) photobioreactor (PBR) in order to evaluate the system performance, including nutrients removal, algae harvesting efficiency and membrane fouling. After 7 days of operation, both systems showed effective nutrients removal. A total of 92.9%, 100% and 98.7% of PO4-P, NH3-N and TN were removed in the PBR integrated with the submerged FO module, and 82%, 96% and 94.8% of PO4-P, NH3-N and TN were removed in the PBR integrated with the side-stream FO module. The better nutrients removal efficiency is attributed to the greater algae biomass in the submerged FO-PBR where in situ biomass dewatering was conducted. The side-stream FO module showed more severe permeate flux loss and biomass loss (less dewatering efficiency) due to algae deposition onto the membrane. This is likely caused by the higher initial water flux associated with the side-stream FO configuration, resulting in more foulants being transported to the membrane surface. However, the side-stream FO module showed better fouling mitigation by simple hydraulic flushing than the submerged FO module, which is not convenient for conducting cleaning without interrupting the PBR operation. Taken together, our results suggest that side-stream FO configuration may provide a viable way to integrate with PBR for a microalgae-based treatment. The present work provides novel insights into the efficient operation of a FO-PBR for more sustainable wastewater treatment and effective microalgae harvesting.
No Parking Detection and Security System using Vehicle Number Plate Recognition

The Automatic Number Plate Recognition System (ANPR) is one among the recent technological innovations in the domain of smart cities. Surveillance cameras are usually installed in different locations across highways and in metropolitan areas for monitoring and reporting purposes. Vehicle number plate detection and recognition in challenging conditions, such as low illumination, unstable weather, and unavoidable noise has increasingly become the focus of the research studies. The proposed work describes a novel system that uses metropolitan security surveillance system to enforce parking restrictions. The captured image is processed and the vehicles are identified by using the Region based Convolution Neural Network (R-CNN) algorithm, which is a well-known method for performing object detection in deep learning domain. It could also be used to enforce traffic laws. The development tool used in this system is Python. The proposed approach provides a feasible solution to the difficult challenges associated with the notion of long-term monitoring.
The impact of COVID-19 on academic aeromobility practices: Hypocrisy or moral quandary?

Abstract Academics have long regarded air travel as vital to pursuing a successful career. Meanwhile, many academics are at the frontline of climate change science and advocate the urgency to reduce greenhouse gas emissions. The conflict between combating global warming and high aeromobility practices traps academics in a loop of hypocrisy. However, COVID-19 presents an opportunity for academics to advance their research and careers with reduced aeromobility. This research investigates how academics have adapted to virtual working experiences during COVID-19 and the implications for establishing changes in aeromobility practices. Informed by the theory of practice change, this paper reports the findings of a comprehensive survey and interview programme in New Zealand. It provides insights into the prospects for reduced aeromobility and the institutional policy frameworks required to embed a new normal, considering the unique circumstances faced by academics working at geographically remote institutions. The findings reveal that instead of being trapped in a loop of hypocrisy, New Zealand academics face a moral quandary in being concerned about climate change and wishing to reduce aeromobility practices, while wanting to avoid compromising career success. Recommendations for academics to face this moral quandary and their institutions to support practice change are proposed.