Miracle-dz/UniFAR-FTUs huggingface dataset:
BSRA: Blockchain-Based Secure Remote Authentication Scheme for Fog-Enabled Internet of Things

The insufficient trustworthiness of fog nodes in fog computing leads to new security and privacy problems in communication between entities. Existing authentication schemes rely on a trusted third party, or assume that fog nodes are trustworthy, or the authentication overhead is high, which is inconsistent with the characteristics of fog computing. To solve the problem of secure communication in the fog computing environment, we propose an efficient blockchain-based secure remote authentication protocol for the fog-enabled Internet of Things (BSRA). Specifically, blockchain is introduced to construct distributed trust for the fog computing environment. Only lightweight cryptographic primitives, such as physical unclonable functions (PUFs) and cryptographic hash functions, are exploited to design the authentication scheme. In addition, we use temporary identities and the authentication-piggybacking-synchronization to ensure the anonymity and effectiveness of the authentication scheme. We conduct security analysis to demonstrate that BSRA can provide guarantees against various known attacks. We also evaluate the performance of BSRA from several aspects, and the results show that BSRA is effective.
Cascaded Generalized Super-Twisting Observer Design for Sensorless PMSM Drives

This brief investigates the use of a new cascaded generalized super-twisting observer (GSTO) for sensorless permanent magnet synchronous motor (PMSM) drives. Specifically, the developed first-stage observer extracts information about internal back-EMF, and then, ensures that the estimation error converges to an arbitrarily small region within a finite time. Meanwhile, the second-stage observer reconstructs the position and speed information synchronously, which can improve the transient performance to a certain extent compared with the arctangent function calculation-based technique. The benefits of the proposed strategy lie in that the cascaded configuration of the two observers minimizes the high-frequency noise of the back-EMF reconstruction system and provides accurate estimations of rotor position and speed. Furthermore, the chattering problem commonly seen in the conventional sliding mode observer (SMO) can be avoided in the presented scheme. Experimental results validate the effectiveness of the proposed methodology.
On the determination of sparse Hessian matrices using multi-coloring

Efficient determination of large sparse Hessian matrices leads to solving many optimization problems. Exploiting sparsity and symmetry of the Hessian matrix can reduce the number of function evaluations required to determine the matrix. This sparse matrix determination problem can be posed as a graph coloring problem. Graph formulation of the problem using an appropriate model can lead to a better exposition of the matrix compression heuristics.
Wind clumping and the wind-wind collision zone in the Wolf-Rayet binary gamma ² Velorum observations at high and low state. XMM-Newton observations at high and low state

We present XMM-Newton observations of γ 2 Velorum (WR 11, WC8+O7.5III, P = 78.53 d), a nearby Wolf-Rayet binary system, at its X-ray high and low states. At high state, emission from a hot collisional plasma dominates from about 1 to 8 keV. At low state, photons between 1 and 4 keV are absorbed. The hot plasma is identified with the shock zone between the winds of the primary Wolf-Rayet star and the secondary O giant. The absorption at low state is interpreted as photoelectric absorption in the Wolf-Rayet wind. This absorption allows us to measure the absorbing column density and to derive a mass loss rate . M = 8 × 10 −6 Myr −1 for the WC8 star. This mass loss rate, in conjunction with a previous Wolf-Rayet wind model, provides evidence for a clumped WR wind. A clumping factor of 16 is required. The X-ray spectra below 1 keV (12 A) show no absorption and are essentially similar in both states. There is a rather clear separation in that emission from a plasma hotter than 5 MK is heavily absorbed in low state while the cooler plasma is not. This cool plasma must come from a much more extended region than the hot material. The Neon abundance in the X-ray emitting material is 2.5 times the solar value. The unexpected detection of C  (25.3 A) and C  (31.6 A) radiative recombination continua at both phases indicates the presence of a cool (∼40 000 K) recombination region located far out in the binary system.
Health-related quality of life of children and adolescents with one vs. multiple disabilities – Are there differences from the parents’ perspective?

ABSTRACT Background Multiple disabilities represent separate entities that cannot be reduced to the sum of disabilities or the main disability. This study compared the health-related quality of life (HRQoL) of children and adolescents with multiple disabilities and those with one developmental disability. We further assessed how comorbidities and guardianship type affected HRQoL. Method On a sample of 190 children and adolescents with developmental disabilities aged 2–18 years (mean age 11.19 years, SD 3.76), we evaluated HRQoL using the PedsQL 4.0 Generic Core Scale (parent proxy-reports). Results Participants with multiple disabilities and participants with one developmental disability statistically significantly differed in all domains of HRQoL, except for emotional functioning. Multiple disabilities resulted in a lower HRQoL. Comorbidities like epilepsy diminished participants’ HRQoL. Guardianship type did not affect HRQoL. Conclusions Disability complexity affects HRQoL. Since each impairment increases difficulties in daily functioning, all existing disorders need to be considered when planning services for children with disabilities.
High-Isolation Tripolarized Metasurface Antenna for Access-Point Applications

In this communication, a high-isolation tripolarized metasurface antenna with a low profile is presented based on characteristic mode analysis (CMA) for indoor access-point applications. To realize triple polarization diversity, two differential-mode (DM) excitations and one multiport common-mode excitation are utilized to excite the shared metasurface. Based on the proposed feeding schemes, two pairs of degenerate characteristic modes (CMs) with broadside radiation and two CMs with radiation nulls at the broadside are selected for different polarizations. In addition, nonuniform unit patches and slot structures are elaborately introduced on the metasurface, which can tune the resonant frequencies of target CMs into the desired band. Finally, the proposed tripolarized metasurface antenna was fabricated and measured. Measured results show that the impedance bandwidth for <inline-formula> <tex-math notation="LaTeX">$x$ </tex-math></inline-formula>- and <inline-formula> <tex-math notation="LaTeX">$y$ </tex-math></inline-formula>-polarization ports can cover 3.4–3.8 GHz, and the <inline-formula> <tex-math notation="LaTeX">$ {z}$ </tex-math></inline-formula>-polarization port can cover 3.4–4.0 GHz. The isolation in the operating band is better than 37 dB. Good diversity characteristics are also validated by the measured radiation patterns.
Stable Inversion Based Precise Tracking for Periodic Systems

Stable inversion based precise tracking for discrete‐time periodically time‐varying square systems is studied. By means of the lifting technique, the time‐varying system is reformulated equivalently to the time‐invariant lifted system that is analyzed for different cases such as the non‐singular case and the singular case. Combining the stable inversion method of these cases with the optimal state transition method for time‐varying systems, precise tracking is achieved from a limited initial time. The tracking performance of the proposed method is validated through simulations.
Generative timbre spaces with variational audio synthesis

Timbre spaces have been used in music perception to study the perceptual relationships between instruments based on dissimilarity ratings. However, these spaces do not generalize, need to be reconstructed for each novel example and are not continuous, preventing audio synthesis. In parallel, generative models have aimed to provide methods for synthesizing novel timbres. However, these systems do not provide an explicit control structure, nor do they provide an understanding of their inner workings and are usually not related to any perceptually relevant information. Here, we show that Variational Auto-Encoders (VAE) can alleviate all of these limitations by constructing variational generative timbre spaces . To do so, we adapt VAEs to create a generative latent space, while using perceptual ratings from timbre studies to regularize the organization of this space. The resulting space allows to analyze novel instruments, while being able to synthesize audio from any point of this space. We introduce a speciﬁc regularization allowing to directly enforce given perceptual constraints or similarity ratings onto these spaces. We compare the resulting space to existing timbre spaces and show that they provide almost similar distance relationships. We evaluate several spectral transforms as input and show that the Non-Stationary Gabor Transform (NSGT) provides the highest correlation to timbre spaces and the best quality of synthesis. Furthermore, we show that these spaces can generalize to novel instruments and can generate any path between instruments to understand their timbre relationships. As these spaces are continuous, we study how the traditional acoustic descriptors behave along the latent dimensions. We show that even though descriptors have an overall non-linear topology, they follow a locally smooth evolution. Based on this, we introduce a method for descriptor-based synthesis and show that we can control the descriptors of an instrument while keeping its timbre structure.
Serum BDNF levels and state anxiety are associated with somatic symptoms in patients with panic disorder

Background We aimed to explore the predictive role of serum BDNF and anxiety-related variables in changes in somatic symptoms post-escitalopram treatment in panic disorder (PD) patients. Methods Ninety PD patients and 99 healthy controls (HCs) were enrolled. PD patients received an 8-week escitalopram treatment. All patients were administered the Panic Disorder Severity Scale–Chinese Version (PDSS-CV) and State-Trait Anxiety Inventory (STAI) to assess panic and anxiety-related symptoms, respectively. Patient Health Questionnaire 15-item scale (PHQ-15) was performed to measure somatic symptoms, and the blood sample was collected to detect serum BDNF levels in all participants. We performed partial correlation analysis and multiple linear regression to explore correlates of PHQ-15 and predictors of PHQ-15 changes post-escitalopram treatment after controlling for age, gender, education levels (set as a dummy variable), the current duration, comorbid AP, and/or GAD. Results Compared to HCs, PD patients had lower serum BDNF levels and higher PHQ-15 scores that could be improved post-escitalopram treatment. Lower baseline STAI state (b = −0.07, p = 0.004), and PDSS-CV scores (b = −0.25, p = 0.007), but higher baseline serum BDNF levels (b = 0.35, p = 0.007) contributed to the prediction of PHQ-15 changes post-escitalopram treatment. Conclusion State anxiety, serum BDNF levels, and panic severity could predict changes in somatic symptoms post-escitalopram treatment, our results highlighted that serum BDNF could serve as a biological indicator for improving somatic symptoms in PD patients.
Filling Pattern Measurements Using Dead-Time Corrected Single Photon Counting

Time-correlated single photon counting (TCSPC) is a versatile tool for various accelerator diagnostics aspects. Amongst others it allows a precise determination of the filling pattern. At the visible light diagnostics port at the Karlsruhe Research Accelerator (KARA), the KIT storage ring, a Single-Photon Avalanche Diode (SPAD) in combination with a histogramming device (PicoHarp) is used. To compensate for possible dead-time effects, a correction scheme was developed and tested successfully. The compensation increases the dynamic range in which accurate measurements are possible and avoids distortion of the measured filling pattern. This contribution presents the experimental setup, as well as a series of benchmark measurements.
Effects of the Hunga Tonga‐Hunga Ha'apai Eruption on MODIS‐Retrieved Sea Surface Temperatures

The eruption of Hunga Tonga‐Hunga Ha'apai (HTHH) volcano on 15 January 2022 injected a great amount of H2O and a moderate amount of SO2 into the stratosphere, producing a pronounced and persistent sulfate aerosol layer centered around the mid‐stratosphere, mostly confined to Southern Hemisphere (SH) tropics. These aerosols affect the Moderate Resolution Imaging Spectroradiometer (MODIS) retrievals of sea surface temperature (SST) where negative biases reached −0.3 K and an annual mean of −0.1 K north of 40°S in the SH. The spatial and temporal evolutions of MODIS SST anomalies are presented. Radiative transfer simulations demonstrate the aerosol effect on MODIS SST retrievals by causing an additional brightness temperature (BT) deficit at 11 μm and a reduction in BT differences since the characteristic of spectral attenuation between 11 and 12 μm is opposite to that of H2O. A correction for HTHH aerosol effects in the retrieval algorithm is therefore desirable.
An association test based on the mixture of zero-inflated Poisson regression models for detecting differential microbial abundance in case-control studies

An association test based on the mixture of zero-inflated Poisson regression models for detecting differential microbial abundance in case-control studies. Maoyu Zhu Advisor: University of Guelph, 2017 Professor Z. Feng Motivation: The human microbial communities play an important role in human health and disease because human metabolism, nutrient intake and energy generation fall under the influence of these communities. Association analysis concerning relative abundances among these communities with status-related outcomes can provide essential information, which can help us to understand the impact that changes in the relative abundances profile can have on disease status. Proper testing of overdispersion and zero-inflated microbiome data is challenging. Existing methods fail to pinpoint the degree of association. Results: In this thesis, we propose a likelihood ratio test for testing the association between the relative abundance of bacteria and disease covariate for microbiome data while using a generalized zero-inflated Poisson regression mixture model. Simulation studies have shown that the likelihood ratio statistic, which examines the null hypothesis that the distribution of the bacterial count arises from healthy individuals and individuals with disease is the same versus the alternative hypothesis that the distribution of the bacterial count arises from healthy individuals and individuals with disease are different, converges to a χ distribution. The power of the likelihood ratio test is also evaluated by our simulation study. The application of our proposed method on the real microbiome data has shown that the associated bacteria at the genus level has different distributions of the bacteria counts between the healthy individuals and individuals with carcinoma. Our proposed method provides a useful tool for identifying differentiate taxonomic abundances underlying different disease status.
Effect of Footwear Type on Biomechanical Risk Factors for Knee Osteoarthritis

Background: Regular walking in different types of footwear may increase the mediolateral shear force, knee adduction moment, or vertical ground-reaction forces that could increase the risk of early development of knee osteoarthritis (OA). Purpose: To compare kinematic and kinetic parameters that could affect the development of knee OA in 3 footwear conditions. Study Design: Controlled laboratory study. Methods: A total of 40 asymptomatic participants performed walking trials in the laboratory at self-selected walking speeds under barefoot (BF), minimalistic (MF), and neutral (NF) footwear conditions. Knee joint parameters were described using discrete point values, and continuous curves were evaluated using statistical parametric mapping. A 3 × 1 repeated-measures analysis of variance was used to determine the main effect of footwear for both discrete and continuous data. To compare differences between footwear conditions, a post hoc paired t test was used. Results: Discrete point analyses showed a significantly greater knee power in NF compared with MF and BF in the weight absorption phase (P < .001 for both). Statistical parametric mapping analysis indicated a significantly greater knee angle in the sagittal plane at the end of the propulsive phase in BF compared with NF and MF (P = .043). Knee joint moment was significantly greater in the propulsive phase for the sagittal (P = .038) and frontal planes (P = .035) in BF compared with NF and MF and in the absorption phase in the sagittal plane (P = .034) in BF compared with MF and NF. A significant main effect of footwear was found for anteroposterior (propulsion, ↑MF, NF, ↓BF [P = .008]; absorption, ↑BF, MF, ↓NF [P = .001]), mediolateral (propulsion, ↑MF, NF, ↓BF [P = .005]; absorption, ↑NF, MF, ↓BF [P = .044]), and vertical (propulsion, ↑NF, BF, ↓MF [P = .001]; absorption, ↑MF, BF, ↓NF [P < .001]) ground-reaction forces. Knee power showed a significant main effect of footwear (absorption, ↑NF, MF, ↓BF [P = .015]; propulsion, ↑MF, NF, ↓BF [P = .039]). Conclusion: Walking in MF without sufficient accommodation affected kinetic and kinematic parameters and could increase the risk of early development of knee OA.
Overview of recent advances in stability of linear systems with time‐varying delays

This study provides an overview and in-depth analysis of recent advances in stability of linear systems with time-varying delays. First, recent developments of a delay convex analysis approach, a reciprocally convex approach and the construction of Lyapunov–Krasovskii functionals are reviewed insightfully. Second, in-depth analysis of the Bessel–Legendre inequality and some affine integral inequalities is made, and recent stability results are also summarised, including stability criteria for three cases of a time-varying delay, where information on the bounds of the time-varying delay and its derivative is totally known, partly known and completely unknown, respectively. Third, a number of stability criteria are developed for the above three cases of the time-varying delay by employing canonical Bessel–Legendre inequalities, together with augmented Lyapunov–Krasovskii functionals. It is shown through numerical examples that these stability criteria outperform some existing results. Finally, several challenging issues are pointed out to direct the near future research.
Implementation and Comparison of Efficient 16-Bit SQRT CSLA Using Parity Preserving Reversible Gate

In Very Large Scale Integration (VLSI) outlines, Carry Select Adder (CSLA) is one of the quickest adder utilized as a part of numerous data processing processors to perform quick number crunching capacities. In this paper we proposed the design of SQRT CSLA using parity preserving reversible gate (P2RG). Reversible logic is emerging field in today VLSI design. In conventional circuits, the logic gates such as AND gate, OR gate is irreversible in nature and computing with irreversible logic results in energy dissipation. This problem can be circumvented by using reversible logic. In ideal condition, the reversible logic gate produces zero power dissipation. The proposed design is efficient in terms of delay as compare to irreversible SQRT CSLA. The simulation is done using Xilinx.
Fever burden within 24 h after hematoma evacuation predicts early neurological deterioration in patients with intracerebral hemorrhage: a retrospective analysis

Background Early neurological deterioration after hematoma evacuation is closely associated with a poor prognosis in patients with intracerebral hemorrhage. However, the relationship between body temperature after hematoma evacuation and early neurological deterioration remains unclear. Therefore, this study aims to explore the possible relationship between body temperature and early neurological deterioration in patients with intracerebral hemorrhage after hematoma evacuation. Methods We retrospectively collected data from patients with cerebral hemorrhage at our institute between January 2017 and April 2022. The Student’s t-test, Mann–Whitney U-test, and χ2 Test and Fisher’s exact test were used to analyze the clinical baseline data. A univariate logistic regression model was used to evaluate the association between the body temperature indices and early neurological deterioration. The predictive power was assessed using the area under the Receiver Operating Characteristic (ROC) curve. The secondary outcome was a poor functional outcome. Results Among 2,726 patients with intracerebral hemorrhage, 308 who underwent hematoma evacuation were included in the present analysis. A total of 82 patients (22.6%) developed early neurological deterioration. Univariate analysis showed that sex (p = 0.041); body temperature at 6 h (p = 0.005), 12 h (p = 0.01), and 24 h (p = 0.008) after surgery; duration of fever (p = 0.008); and fever burden (p < 0.001) were associated with early neurological deterioration. Multivariate logistic regression showed that fever burden was independently associated with early neurological deterioration (OR = 1.055 per °C × hour, 95%CI 1.008–1.103, p = 0.020). ROC showed that fever burden (AUC = 0.590; 95%CI: 0.514–0.666) could predict the occurrence of early neurological deterioration. Conclusion Fever burden is associated with early neurological deterioration in intracerebral hemorrhage patients undergoing hematoma evacuation. Our findings add to previous evidence on the relationship between the fever burden and the occurrence of early neurological deterioration in patients with intracerebral hemorrhage. Future studies with larger sample sizes are required to confirm these findings.
Customer Targeting for Load Flexibility via Resident Behavior Segmentation

Caused by the widespread of renewable energy resources, oversupply and overdesign of reserve capacity are serious concerns in electrical power system. Hence, power system needs load flexibility (LF) to mitigate the concerns. Despite utilities’ efforts to aggregate LF for residential loads, aggregated LF operations are typically inefficient due to load uncertainties caused by individual customers’ varying behaviors. Therefore, in this study, a novel customer targeting model for LF participation is proposed based on resident behavior analysis. The proposed scheme comprises a resident behavior segmentation model (RBSM) performing deep-learning-based and probabilistic clustering and a virtual LF operation model (VLFOM) considering human comfort. Simulations were conducted in a residential environment in San Diego, California. The superior performance of RBSM was confirmed through internal clustering evaluation methods. Accordingly, the results of the VLFOM model confirmed the criteria of resident behaviors for adequate LF participation. The experiment results present that the proposed model is economically and environmentally effective to the LF operation for utilities. Finally, implications of LF aggregation based on uncertainty assessment and meaningful suggestions of the settlement design for future LF expansion are presented.