Miracle-dz/UniFAR-FTUs huggingface dataset:
Iterative Signal Processing for Integrated Sensing and Communication Systems

Integrated sensing and communication (ISAC), with sensing and communication sharing the same wireless resources and hardware, has the advantages of high spectrum efficiency and low hardware cost, which is regarded as one of the key technologies of the fifth generation advanced (5G-A) and sixth generation (6G) mobile communication systems. ISAC has the potential to be applied in the intelligent applications requiring both communication and high accurate sensing capabilities. The fundamental challenges of ISAC system are the ISAC signal design and ISAC signal processing. However, the existing ISAC signal has low anti-noise capability. And the existing ISAC signal processing algorithms have the disadvantages of quantization errors and high complexity, resulting in large energy consumption. In this paper, phase coding is applied in ISAC signal design to improve the anti-noise performance of ISAC signal. Then, the effect of phase coding method on improving the sensing accuracy is analyzed. In order to improve the sensing accuracy with low-complexity algorithm, the iterative ISAC signal processing methods are proposed. The proposed methods improve the sensing accuracy with low computational complexity, realizing energy efficient ISAC signal processing. Taking the scenarios of short distance and long distance sensing into account, the iterative two-dimensional (2D) fast Fourier transform (FFT) and iterative cyclic cross-correlation (CC) methods are proposed, respectively, realizing high sensing accuracy and low computational complexity. Finally, the feasibility of the proposed ISAC signal processing methods are verified by simulation results.
Forecasting commodity prices in Brazil through hybrid SSA-complex seasonality models

Paper aims: To predict monthly corn, soybean, and sugar spot prices in Brazil using hybrid forecasting techniques. Originality: This study combines the Singular Spectrum Analysis with different forecasting methods. Research method: This paper presents a set of hybrid forecasting approaches combining Singular Spectrum Analysis (SSA) with different univariate time series methods, ranging from complex seasonality methods to machine learning and autoregressive models to predict monthly corn, soybean, and sugar spot prices in Brazil. We carry out a range of out-of-sample forecasting experiments and use a comprehensive set of forecast evaluation metrics. We contrast the performance of the proposed approaches with that of a range of benchmark models. Main findings: The results show that the proposed hybrid models present better performances, with the hybrid SSA-neural network approach providing the most competitive results in our sample. Implications for theory and practice: Forecasting agricultural prices is of paramount importance to assist producers, farmers, and the industry in decision-making processes.
Construction of linearized kinetic models for gaseous mixtures and molecular gases

A simple method of construction of linearized kinetic models is proposed which is based upon the equivalence of moments of the Nth‐order modeled collision operator and the moments of the full collision operator calculated with the Nth‐order approximation to the distribution function. This method is used to construct a third‐order model of the linearized cross‐collision operator for a general multicomponent monatomic gaseous mixture, not restricted to Maxwell molecules. In addition, this method is used to extend the Hanson‐Morse diatomic gas model of the Wang Chang‐Uhlenbeck collision operator to a polyatomic gas. Also presented is a new method of formally extending the Gross‐Jackson modeling procedure to multicomponent monatomic mixtures. It is shown that the method of constructing mixture models based on the equivalence of moments is identical to this new procedure. In addition, the Gross‐Jackson modeling procedure recently developed for mixtures by Boley and Yip is analyzed. It is shown that, under a ce.
Pathogenic Th2 Cytokine Profile Skewing by IFN-γ-Responding Vitiligo Fibroblasts via CCL2/CCL8

Purpose: Vitiligo is a T cell-mediated skin depigmentation disease. Though treatments arresting disease progression and inducing repigmentation are available, the efficacy of these options is often limited and poorly sustained. How stromal signals contribute to the interferon-γ-dominant skin niches is unclear. This study aims to determine how fibroblasts participate in the IFN-γ-dominant vitiligo niche. Patients and methods: Mouse vitiligo models were established. Fibroblasts from control and vitiligo mice were extracted for RNA sequencing. In vitro IFN-γ stimulation was performed to verify the JAK-STAT pathway by qPCR and Western blot. T cell polarization with chemokines was measured by flow cytometry. Protein levels in tissues were also examined by IHC. Results: The vitiligo mouse model recapitulates the human CD8-IFN-γ pathway. RNA sequencing revealed elevated chemokine CCL2 and CCL8 in vitiligo fibroblast, which may be regulated by the JAK-STAT signaling. Such phenomenon is verified by JAK inhibitor peficitinib in vitro. Moreover, CCL2 addition into the naïve T polarization system promoted type 2 cytokines secretion, which represents a hallmark of vitiligo lesions. Conclusion: Dermal fibroblasts, a principal constituent of skin structure, respond to IFN-γ by skewing T cells towards a type 2 cytokine profile via CCL2 and CCL8, which can be abrogated by JAK inhibitor peficitinib.
Effectiveness of Augmented and Virtual Reality-Based Interventions in Improving Knowledge, Attitudes, Empathy and Stigma Regarding People with Mental Illnesses—A Scoping Review

Interventions adopting augmented and virtual reality (AR/VR) modalities allow participants to explore and experience realistic scenarios, making them useful psycho-educational tools for mental illnesses. This scoping review aims to evaluate the effectiveness of AR/VR interventions in improving (1) knowledge, (2) attitudes, (3) empathy and (4) stigma regarding people with mental illnesses. Literature on published studies in English up till April 2022 was searched within several databases. Sixteen articles were included. The majority of studies were conducted in the West (93.8%), within undergraduates (68.8%) but also amongst high school students, patients, caregivers, public including online community, and covered conditions including psychotic illnesses, dementia, anxiety and depression. A preponderance of these included studies which employed AR/VR based interventions observed improvements in knowledge (66.7%), attitudes (62.5%), empathy (100%) and reduction of stigma (71.4%) pertaining to people with mental illnesses. In the context of relatively limited studies, extant AR/VR based interventions could potentially improve knowledge, attitudes, empathy and decrease stigma regarding people with mental illness. Further research needs to be conducted in larger and more diverse samples to investigate the relatively beneficial effects of different AR/VR modalities and the durability of observed improvements of relevant outcomes of interests over time for different mental conditions.
Automatic continuity of n-homomorphisms between FrÉchet algebras

We impose a condition on a commutative regular Fréchet algebra (A, (pm )) to ensure that A/kerpm is a Fréchet Q-algebra. This implies that if θ is an n-homomorphism on certain Fréchet algebras (A, (pm )) into semisimple commutative Fréchet algebras (B,(qm)) such that θ(kerpm) ⫅ kerqm, for large enough m, then θ is continuous. We also show that if A is a Fréchet Q-algebra, B is a semisimple Fréchet algebra, θ: A → B is a dense range n-homomorphism such that θ(A) is factorizable, and the spectral radius vB is continuous on the separating space (θ), then θ is automatically continuous.
The Approximate Integral Equation for a Cylindrical Scatterer Has No Solution

Using an analytic-continuation argument, it is shown that the Hallén-type integral equation for the current distribution on an unloaded receiving antenna does not have a solution if the approximate kernel is used. Generalizations and consequences of this nonsolvability are discussed. The aforementioned argument does not apply when the exact kernel, which is logarithmically singular, is used.
Hydrocode modeling of oblique impacts: The fate of the projectile

Abstract— All impacts are oblique to some degree. Only rarely do projectiles strike a planetary surface (near) vertically. The effects of an oblique impact event on the target are well known, producing craters that appear circular even for low impact angles (>15° with respect to the surface). However, we still have much to learn about the fate of the projectile, especially in oblique impact events. This work investigates the effect of angle of impact on the projectile.
In Vitro and In Vivo Studies of Heraclenol as a Novel Bacterial Histidine Biosynthesis Inhibitor against Invasive and Biofilm-Forming Uropathogenic Escherichia coli

Globally, urinary tract infections (UTIs) are one of the most frequent bacterial infections. Uropathogenic Escherichia coli (UPEC) are the predominant etiological agents causing community and healthcare-associated UTIs. Biofilm formation is an important pathogenetic mechanism of UPEC responsible for chronic and recurrent infections. The development of high levels of antimicrobial resistance (AMR) among UPEC has complicated therapeutic management. Newer antimicrobial agents are needed to tackle the increasing trend of AMR and inhibit biofilms. Heraclenol is a natural furocoumarin compound that inhibits histidine biosynthesis selectively. In this study, for the first time, we have demonstrated the antimicrobial and antibiofilm activity of heraclenol against UPEC. The drug reduced the bacterial load in the murine catheter UTI model by ≥4 logs. The drug effectively reduced bacterial loads in kidney, bladder, and urine samples. On histopathological examination, heraclenol treatment showed a reversal of inflammatory changes in the bladder and kidney tissues. It reduced the biofilm formation by 70%. The MIC value of heraclenol was observed to be high (1024 µg/mL), though the drug at MIC concentration did not have significant cytotoxicity on the Vero cell line. Further molecular docking revealed that heraclenol binds to the active site of the HisC, thereby preventing its activation by native substrate, which might be responsible for its antibacterial and antibiofilm activity. Since the high MIC of heraclenol is not achievable clinically in human tissues, further chemical modifications will be required to lower the drug’s MIC value and increase its potency. Alternatively, its synergistic action with other antimicrobials may also be studied.
Approximating Fredholm operators on a nonseparable Hilbert space

Abstract This paper obtains a simple formula for the distance from a given operator to the set of invertible operators without requiring the underlying space to be separable. That formula is used to compute the distance to the Fredholm operators with a given index. These results require the further study of the concepts of essential nullity and essential deficiency, which permitted us to characterize the closure of the invertible operators. We also introduce a parameter called the modulus of Fredholmness.
Influence of interactions on magnetization behavior of arrays of nanostructures with uniaxial anisotropy

A semianalytical model is presented for representing the magnetization switching in arrays of nanostructures with uniaxial anisotropy that includes both the dipolar interactions between structures in the array and a distribution of switching fields for the structures within the arrays. The net magnetic field experienced by each individual structure is the sum of the externally applied field and the local field from the other structures. Here the local field was calculated by subdividing each nanostructure into discrete magnetic moments. The field dependence of each structure within the array was represented by assigned switching behavior. The simplest behavior assumed a structure was wholly reversed at a given axial field (square switching), while more complex behavior was also implemented using both a Stoner–Wohlfarth representation of switching and switching behavior that included a zero magnetization state to represent a vortex state. A distribution of switching fields within an array was incorporated .
Estimating Historical Heating and Cooling Needs. Per Capita Degree Days

Abstract Time series of approximate United States average annual per capita heating and cooling degree days for the years 1895–1983 are presented. The data reflect the combined effects of climate fluctuations and population shifts, and can be used in studies of historical energy demand for heating and cooling at the national level. The development of the series is described, and the resulting data are used to show the effect of the north-to-south population shift of recent decades on the country's heating and cooling needs. Finally, other research topics are suggested for which the data may prove useful.
CONDUCTION AND 1/F NOISE ANALYSIS IN AMORPHOUS SILICON THIN-FILM TRANSISTORS

Conduction and low‐frequency noise are analyzed in the channel of hydrogenated amorphous silicon (a‐Si:H) thin‐film transistors. 1/f noise expressions are proposed starting from a simple conduction model describing drain current in the ohmic range. Carrier fluctuations (ΔN model) and mobility fluctuations (Δμ model) are investigated. For long‐channel transistors the conduction is quite similar to crystalline metal–oxide–semiconductor field‐effect transistors but involving low mobility values. The 1/f noise behavior is analyzed by mobility fluctuations as predicted by Hooge’s theory. For small channel transistors a crowding effect appears and access series resistances affect the conduction. The excess noise is then mainly controlled by these resistances when large gate voltages VGS are applied.
Applying a direct current bias to superconducting microwave resonators by using superconducting quarter wavelength band stop filters

We have designed a superconducting quarter wavelength band stop filter which provides a high attenuation at approximately 7 GHz. Such filters were used as dc bias lines applied to whole wavelength and half wavelength superconducting resonators at two different extremes: voltage node and voltage antinode. The results obtained indicate that this filter can apply dc bias to arbitrary length superconducting coplanar waveguide resonators while maintaining high quality factor, Q∼15 000−18 000.
A Technique of Studying Sums of Central Cantor Sets

Abstract This paper is concernedwith the structure of the arithmetic sum of a finite number of central Cantor sets. The technique used to study this consists of a duality between central Cantor sets and sets of subsums of certain infinite series. One consequence is that the sum of a finite number of central Cantor sets is one of the following: a finite union of closed intervals, homeomorphic to the Cantor ternary set or an $M$ -Cantorval.
The Effect of Earnings Management, Capital Intensity, Firm Size, Fiscal Loss Compensation on Tax Avoidance

Effect of Earnings Management, Capital Intensity, Firm Size, and Fiscal Loss Compensation on Tax Avoidance (Study on Food and Beverage Companies listed on the Indonesia Stock Exchange in 2015-2019). This study aims to obtain evidence on the effect of earnings management, firm size, capital intensity, and compensation for tax losses on tax avoidance. In this study, using purposive sampling method to show the sample. The population in this thesis are manufacturing companies with the food and beverage sector with a population of 80 companies listed on the Indonesia Stock Exchange (IDX). With the selection of criteria, there is a total sample of 16 companies in an observation period of 5 years starting from 2015-2019. In this observation, tax avoidance is calculated through the formulation of the ETR. The tester for the hypothesis in this observation uses multiple regression analysis techniques. The results of this observation show that earnings management, firm size, and tax loss compensation affect tax avoidance. But capital intensity can not affect tax avoidance.
Preparation and Performance of AgNWs/PDMS Film-Based Flexible Strain Sensor

Flexible strain sensors are widely used in the fields of personal electronic equipment and health monitoring to promote the rapid development of modern social science and technology. In this paper, silver nanowires (AgNWs) prepared via the polyol reduction method were used to construct a flexible strain sensor. The AgNWs/PDMS film was obtained by transfer printing using AgNWs as a conductive layer and polydimethylsiloxane (PDMS) as a flexible substrate. The morphology of AgNWs was characterized by SEM and TEM. The aspect ratio of the AgNWs was more than 700. The strain sensitivity factor of the sensor was 2.8757, with a good linear relationship between the resistance and the strain. Moreover, the strain sensor showed good response results in human activity monitoring and the LED lamp response test, which provides a new idea for the construction of flexible wearable devices.
Effect of Post-Printing Cooling Conditions on the Properties of ULTEM Printed Parts

This paper aimed to estimate the effect of post-printing cooling conditions on the tensile and thermophysical properties of ULTEM® 9085 printed parts processed by fused deposition modeling (FDM). Three different cooling conditions were applied after printing Ultem samples: from 180 °C to room temperature (RT) for 4 h in the printer (P), rapid removal from the printer and cooling from 200 °C to RT for 4 h in the oven (O), and cooling at RT (R). Tensile tests and dynamic mechanical thermal analysis (DMTA) were carried out on samples printed in three orthogonal planes to investigate the effect of the post-printing cooling conditions on their mechanical and thermophysical properties. Optical microscopy was employed to relate the corresponding macrostructure to the mechanical performance of the material. The results obtained showed almost no difference between samples cooled either in the printer or oven and a notable difference for samples cooled at room temperature. Moreover, the lowest mechanical performance and sensitivity to the thermal cooling conditions were defined for the Z printing direction due to anisotropic nature of FDM and debonding among layers.
A Multivariate Additive Inflation Approach to Improve Storm‐Scale Ensemble‐Based Data Assimilation and Forecasts: Methodology and Experiment With a Tornadic Supercell

Ensemble‐based convective‐scale radar data assimilation commonly suffers from an underdispersive background ensemble. This study introduces a multivariate additive‐inflation method to address such deficiency. The multivariate additive inflation (AI) approach generates coherent random perturbations drawn from a newly constructed convective‐scale static background error covariance matrix for all state variables including hydrometeors and vertical velocity. This method is compared with a previously proposed univariate AI approach, which perturbs each variable individually without cross‐variable coherency. Comparisons are performed on the analyses and forecasts of the 8 May 2003 Oklahoma City tornadic supercell. Within assimilation cycles, the multivariate approach is more efficient in increasing reflectivity spread and thus has a reduced spinup time than the univariate approach; the additional inclusion of hydrometeors and vertical velocity results in more background spread for both reflectivity and radial velocity. Significant differences among AI experiments also exist in the subsequent forecasts and are more pronounced for the forecasts initialized from the earlier assimilation cycles. The multivariate approach yields better forecasts of low‐level rotation, reflectivity distributions, and storm maintenance for most lead times. The additional inclusion of hydrometeor and vertical velocity in the multivariate method is beneficial in forecasts. Conversely, the additional inclusion of hydrometeor and vertical velocity in the univariate method poses negative impacts for the majority of forecast lead times.
On the Doppler Shifts of Solar Ultraviolet Emission Lines

We examine emission-line profiles observed with the Solar Ultraviolet Measurement of Emitted Radiation (SUMER) instrument during the roll of the SOHO spacecraft on 1997 March 20. SUMER data were acquired in selected wavelength bands including lines from the low chromosphere to the corona. Our main aim is to determine the center-to-limb behavior of emission lines formed in the chromosphere, transition region, and corona, especially of the observed Doppler shifts, to try to form a consistent picture of the basic kinematic properties of the emitting plasmas. To achieve this we combine the roll data with data from the full disk discussed elsewhere and fitted Gaussian profiles to the cores of the line profiles. The Doppler-shift data at large spatial scales (>50'') clearly reveal center-to-limb redshift behavior consistent with a cos ϑ variation in all transition region lines. The three "coronal" lines in the data set (of Ne VIII and Mg X) reveal center-to-limb behavior consistent with disk-center blueshifts, in contradiction to some previous work. The redshift to blueshift transition occurs at electron temperatures of about 5 × 105 K. Furthermore, we present evidence for an outflow of the fast solar wind from the coronal holes throughout the whole transition region. These results confirm and extend earlier work and point toward a (re-) measurement of rest wavelengths of lines formed at coronal temperatures in the laboratory. Together these results provide a firmer observational foundation for the development of classes of models to account for the well-known redshifts and point to the need to develop models that can also account for the coronal-line blueshifts.
Properties of singular vectors using convective available potential energy as final time norm

We study the feasibility of using the singular vector technique to create initial condition perturbations for shortrange ensemble prediction systems (SREPS) focussing on predictability of severe local storms and in particular deep convection. For this a newfinal time semi-norm based on the convective available potential energy (CAPE) is introduced. We compare singular vectors using the CAPE-norm with SVs using the more common total energy (TE) norm for a 2-week summer period in 2007, which includes a case of mesoscale extreme rainfall in the south west of Finland. The CAPE singular vectors perturb the CAPE field by increasing the specific humidity and temperature of the parcel and increase the lapse rate above the parcel in the lower troposphere consistent with physical considerations. The CAPE-SVs are situated in the lower troposphere. This in contrast to TE-SVs with short optimization times which predominantly remain in the high troposphere. By examining the time evolution of the CAPE singular values we observe that the convective event in the south west of Finland is clearly associated with high CAPE singular values.