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Age-related hearing loss (ARHL) is a common sensory impairment with complex underlying mechanisms. In our previous study, we performed a meta-analysis of genome-wide association studies (GWAS) in mice and identified a novel locus on chromosome 18 associated with ARHL specifically linked to a 32 kHz tone burst stimulus. Consequently, we investigated the role of Formin Homology 2 Domain Containing 3 (Fhod3), a newly discovered candidate gene for ARHL based on the GWAS results. We observed Fhod3 expression in auditory hair cells (HCs) primarily localized at the cuticular plate (CP). To understand the functional implications of Fhod3 in the cochlea, we generated Fhod3 overexpression mice (Pax2-Cre+/-; Fhod3Tg/+) (TG) and HC-specific conditional knockout mice (Atoh1-Cre+/-; Fhod3fl/fl) (KO). Audiological assessments in TG mice demonstrated progressive high-frequency hearing loss, characterized by predominant loss of outer hair cells, and a decreased phalloidin intensities of CP. Ultrastructural analysis revealed loss of the shortest row of stereocilia in the basal turn of the cochlea, and alterations in the cuticular plate surrounding stereocilia rootlets. Importantly, the hearing and HC phenotype in TG mice phenocopied that of the KO mice. These findings suggest that balanced expression of Fhod3 is critical for proper CP and stereocilia structure and function. Further investigation of Fhod3 related hearing impairment mechanisms may lend new insight towards the myriad mechanisms underlying ARHL, which in turn could facilitate the development of therapeutic strategies for ARHL.

High‐frequency dielectric materials have been widely and rapidly applied in areas such as automotive radar, Internet of Things, artificial intelligence, and quantum computing. Currently, the challenge in high‐frequency dielectric materials lies in reducing the dielectric constant (Dk) and dielectric loss (Df) without sacrificing its mechanical properties. This study addresses this challenge by introducing air, as the most common "low dielectric factor," into the polymer matrix in the form of hollow glass microspheres. Meanwhile, the reactive vinyl groups were also introduced onto the surface of the hollow glass microspheres, enabling an interfacial chemical reaction between the side vinyl groups of polybutadiene and its surface so that the organic–inorganic interface compatibility and interface peel strength are simultaneously improved. Consequently, the minimum Dk of 1.29 and Df of 0.0012 in 3–18 GHz are achieved, and the interface peel strength also reaches 0.65 N/mm. Molecular dynamics simulations, analysis of dielectric properties, and interface peel strength reveal the influence of hollow glass microspheres' morphology and chemical structure on their high‐frequency dielectric performance and adhesive strength. This paper provides effective strategies for the structural design and preparation of high‐frequency, low‐dielectric composites, contributing to the further development of next‐generation microwave communication devices towards higher frequencies and faster information transmission. [ABSTRACT FROM AUTHOR]

In the absence of high-frequency visual observation, low-resolution (LR) targets (e.g., objects, human body keypoints) are intrinsically difficult to detect in unconstrained images. This challenge can be further exasperated by typical downsampling operations (e.g., pooling, stride) of existing deep networks (e.g., CNNs). To tackle this challenge, in this work, we introduce a generic, High-Frequency Information Preservation (HFIP) block as a replacement for existing downsampling operations. It is composed of two key components: (1) the decoupled high-frequency learning component, which extracts the high-frequency information along the vertical and horizontal directions separately, and (2) the dilated frequency-aware channel correlation component, which decomposes the input feature map into multiple smaller ones in a dilated manner, concatenates them by channel, and then correlates the combined channels in the frequency space. Our module can generally be integrated into existing network architectures for target detection (e.g., YOLO, HRNet). Extensive experiments on low-resolution human pose estimation and object detection tasks show that our HFIP technique can generally boost the performance of state-of-the-art detection models significantly, e.g., improving the object detection accuracy of YOLOv5s by an absolute margin of 3.30% in mAP under a resolution of 640 × 640 compared to the COCO benchmark. [ABSTRACT FROM AUTHOR]

The time-harmonic Maxwell equations at high wavenumber k in domains with an analytic boundary and impedance boundary conditions are considered. A wavenumber-explicit stability and regularity theory is developed that decomposes the solution into a part with finite Sobolev regularity that is controlled uniformly in k and an analytic part. Using this regularity, quasi-optimality of the Galerkin discretization based on Nédélec elements of order p on a mesh with mesh size h is shown under the k-explicit scale resolution condition that (a) kh/p is sufficient small and (b) p / ln k is bounded from below. [ABSTRACT FROM AUTHOR]

The preface to the Time Series Special Issue of the Journal of Official Statistics discusses the challenges faced by official statistics agencies in publishing and analyzing time series data in the current era. It highlights the impact of technological advancements, declining survey response rates, and the need for timely data. The preface also mentions the benefits of new technologies and methodologies in addressing these challenges, emphasizing the importance of innovation in mathematical statistics and data science. The document provides a summary of eleven research papers in the special issue, covering topics such as temporal disaggregation, crisis identification, seasonal adjustment, and nowcasting. The articles address various methodological and empirical issues related to time series analysis, offering insights into the future directions of research in this field. [Extracted from the article]

The high-frequency decay parameter (κ) is investigated using the three-component broadband seismograms from 306 earthquakes with ML 3.1–5.6 recorded at nine Iranian National Broadband Seismic Network (BIN) stations in the Alborz region and adjacent areas. The individual κ values are calculated for both the horizontal and vertical components of each record. The estimated mean horizontal and vertical κ values are 0.051 and 0.035 s, respectively, indicating slightly lower attenuation of high-frequency energy on the vertical component than the horizontal one. The dependence of the kappa values on path and source parameters such as distance, magnitude, and focal mechanism are also investigated. A clear increasing trend is observed for κ values with hypocentral distances for horizontal and vertical components. The zero-distance kappa (κ0) values for the nine BIN stations are evaluated, and a mean value of 0.013 s is estimated, which is close to the values expected for generic rock sites. The obtained κ values show no significant correlation with the earthquake size in the magnitude range of our events. Furthermore, the κ values are found to be fairly similar for all faulting types, with a slight decrease in κ for strike-slip events; hence, the kappa values are deemed as independent of faulting type. [ABSTRACT FROM AUTHOR]

With the increasing demand for high‐performance printed circuit boards (PCBs) in the 6G communication era, dielectric substrate materials must exhibit a low dielectric constant (Dk), low dielectric loss (Df), and high dimensional stability. In this study, a series of bismaleimide‐incorporated poly(phenylene ether) resins (PPE‐BMI) with varying bismaleimide (BMI) crosslinker contents is developed, exhibiting significantly enhanced dielectric properties and dimensional stability, owing to the restricted polymer chain mobility and increased crosslinking density. Dielectric property measurements reveal that the PPE‐BMI resins exhibit low Dk and Df values at frequencies above 100 GHz, while maintaining an excellent dielectric performance even after an 85 °C/85% relative humidity reliability test. A significant reduction in the coefficient of thermal expansion is observed with an increase in the BMI content. Molecular dynamics simulations are employed to clarify the role of BMI crosslinkers in reducing the free volume, enhancing the crosslinking in the PPE (poly(phenylene ether)) matrix, and influencing the thermophysical properties of PPE‐BMI. The infiltration of PPE‐BMI into glass fabrics and liquid crystal fabrics highlights their potential for practical use in advanced PCB applications operating at high frequencies. [ABSTRACT FROM AUTHOR]

Introduction Case Report Conclusion Pain management in patients with complete spinal cord injury is complex.We report a successful case of managing neuropathic, phantom limb, and back pain below the level of spinal cord injury (T5 American Spinal Injury Association [ASIA] A) using a 10 kHz high‐frequency spinal cord stimulator (SCS) over a 6‐month follow‐up period.The effectiveness of this approach may be attributed to its ability to modulate supraspinal pain processing, allowing for targeted relief of various pain mechanisms below the level of injury. [ABSTRACT FROM AUTHOR]

Transcutaneous electrical stimulation with repetitive bursts of a kilohertz carrier frequency is thought to be less painful than conventional pulsed currents by reducing the sensitivity of pain receptors. However, no purported benefit has been shown unequivocally. We compared the effects of carrier‐frequency stimulation and conventional stimulation on pain tolerance and the thresholds for sensory and motor axons in twelve participants. The ulnar nerve was stimulated transcutaneously with a conventional single pulse and 5 and 10 kHz carrier‐frequency waveforms that had 5 and 10 pulses, respectively, when delivered in bursts of ∼1 ms duration. Phase durations were adjusted across waveform types to match the total charge for a given current amplitude. Single bursts of stimulation were delivered from 1 mA up until no longer tolerable. This was repeated with repetitive bursts of stimulation at 20 Hz for 1 s. Participants tolerated higher current amplitudes with both carrier‐frequency waveforms than conventional stimulation, with repetitive bursts more painful than single bursts. However, compared to conventional stimulation, carrier‐frequency waveforms required more current to produce sensory and motor‐threshold responses and to obtain a maximal motor response (Mmax). When the current at pain tolerance was normalised to the current at Mmax, participants tolerated lower stimulus intensities with carrier‐frequency waveforms than conventional stimulation. These findings indicate that there is little to no benefit in using carrier‐frequency waveforms to minimise the discomfort from electrical stimulation as the increase in stimulus intensity at pain tolerance is more than offset by reduced effectiveness in the activation of sensory and motor axons. Key points: Transcutaneous electrical stimulation with repetitive bursts of a kilohertz carrier‐frequency waveform is thought to be less painful than conventional pulsed currents.For ulnar nerve stimulation, when stimulus waveforms were matched for total phase charge, participants tolerated higher current amplitudes with carrier‐frequency stimulation than conventional stimulation.However, compared to conventional stimulation, carrier‐frequency waveforms required more current to produce a threshold response in both sensory and motor axons and to produce a maximal motor response (Mmax).When current at pain tolerance was normalised to current at Mmax, participants tolerated lower stimulus intensities with carrier‐frequency waveforms than conventional stimulation.Carrier‐frequency waveforms provide little to no benefit in minimising the discomfort from transcutaneous electrical stimulation as the increase in stimulus intensity at pain tolerance is more than offset by reduced effectiveness in activating sensory and motor axons. [ABSTRACT FROM AUTHOR]

The samples including Li 0.1 Co 0.8 Fe 2. 1 O 4 (LCFO) spinel ferrite (SF) and LCFO SF/graphene oxide (GO = 10 wt%, 15 wt%, and 20 wt%) nanocomposite were fabricated via the self-ignition route by following the bath ultra-sonication method. Their structural, morphological, and compositional properties were analyzed using X-ray diffraction (XRD), Fourier transform infrared (FTIR) spectroscopy, scanning electron microscopy (SEM), Transmission electron microscopy (TEM), Energy-dispersive X-ray (EDX) spectroscopy, respectively. Moreover, the dielectric and magnetic properties at 300 K were studied using an impedance analyzer (IA) meter and vibrating sample magnetometer (VSM), respectively. All LCFO SF and GO-based LCFO nanocomposites exhibited a pure spinel matrix. The crystallite size was increased by the GO addition in the LCFO SF sample. The morphological analysis showed the non-uniform distribution of particles. The dielectric constant and loss exhibited behaviour consistent with Maxwell-Wagner interfacial polarization. The low tangent loss was observed at high frequency and ac conductivity analysis was increased with increasing the GO content. A slight enhancement in saturation magnetization was observed at 300 K with the addition of GO in LCFO SF. Hence, doping with GO offers a means to tune the dielectric, and magnetic response of the LCFO SF sample and is the best candidate for potential high-frequency application. [Display omitted] • The LCFO SF and LCFO/GO nanocomposites were prepared via the self-ignition route with an ultra-sonication technique. • The crystallite size was increased from 30 nm to 54 nm. • FTIR analysis along with XRD analysis also confirmed the spinel matrix. • SEM and TEM micrographs indicated the non-uniform distribution and agglomeration with the increasing GO. • The increase in GO leads to an improvement in the dielectric response. • The saturation magnetization was increased with the addition of GO. • The combination of LCFO SF with GO enhanced the dielectric, and magnetic properties, offering a candidate for high-frequency applications. [ABSTRACT FROM AUTHOR]

In this study, we employed a high‐frequency‐driven thin‐film magnetic sensor to precisely measure the magnetic near field with enhanced spatial resolution, a challenge often faced by conventional loop antennas. Our study introduced an innovative approach utilizing this magnetic sensor to assess the magnetic near field in wireless power transfer systems, comparing its performance against that of a loop antenna. Our findings demonstrate that the magnetic sensor achieves its peak signal‐to‐noise ratio at a DC bias field of 4.7 Oe and carrier frequency of 0.5 GHz, boasting a detection limit for magnetic fields of ~0.4 A/m. Moreover, the magnetic field trend measured by the magnetic sensor closely aligns with simulation results, exhibiting sharper changes around the center compared to the loop antenna. These results highlight the superior sensitivity and spatial resolution of the magnetic sensor over conventional loop antennas. By enhancing the reliability of electronic systems across diverse applications, these sensors pave the way for advanced EMI/EMC evaluation techniques. © 2024 Institute of Electrical Engineers of Japan and Wiley Periodicals LLC. [ABSTRACT FROM AUTHOR]

Altcoins are alternative types of coins under cryptocurrency, apart from traditional Bitcoins, for which predicting the price movement presents a multifaceted challenge deeply rooted in the volatile nature of the cryptocurrency market. This study compares and analyzes different Machine Learning (ML) and Deep Learning (DL) models for price movement prediction through diverse data sources like Bitcoin prices, social media sentiments, and news sentiments, apart from different socio-economic factors specific to USA geography due to its maturity on use of Altcoins, with temporal scope spanning from 2016 to 2022 collating over 77 M tweets and news items. Ethereum, Binance, XRP, Cardano, Monero, Tron, Stellar, and Litecoin, were considered for experimentation across widely used algorithms like Gradient Boosting, Naive Bayes, Decision Trees, Neural Networks, and the like, with different day-length lags ranging up to 4 days. Highly relevant features were selected using Random Forest selection method and highly correlated features have been removed before the modeling. Accuracy for price movement prediction models varied from 71.03% for Ethereum to 66.14% for Stellar, which were better by 15–20% as compared to percentage benchmarking done by literature to be ranging around 50 s and 60 s. For the model validation, sensitivity analysis involving day-wise lag analysis, and different data splits (based on size and months) were considered, which was stable for the high performing models. Further, an interesting result was observed during the study. In order of priority, Bitcoin prices, social media sentiments, and news sentiments significantly impact altcoin price movement. This implies that by studying the Bitcoin price movement and market sentiments, investors can make wise decisions towards altcoin investments. This study holds significance for researchers and practitioners to understand the impact in the trading market of cryptocurrency and help an investor diversify their portfolio. The findings will be helpful for Algo Trading Platforms, Financial Advisors, Trading Experts, Industry Experts, Researchers, and Scholars. [ABSTRACT FROM AUTHOR]

Over the past 50 years, concentration‐discharge (cQ) relationships have been widely used to analyse water quality dynamics. Nowadays improved availability of concentration (c) and discharge (Q) data at different spatial and temporal scales have led to a high popularity of cQ applications. However, despite their widespread use, we see persistent challenges in the integration of cQ relationships across temporal scales, and in the identification of the encoded processes. In this commentary, we show that different catchment processes may lead to similar cQ responses resulting in a lack of clear causality. We emphasise that cQ relationships applied at different time scales integrate different parts of the catchment and may, therefore, convey different information. Finally, we advocate for the careful use of cQ relationship as one, but not the only, tool in addressing ecohydrological questions. [ABSTRACT FROM AUTHOR]

Conventional pairs trading strategies (PTS) exploit the mean-reverting nature of stock pairs with stationary value processes. This paper elevates PTS by integrating trend-stationary value processes, thereby enhancing profitability and expanding trading opportunities. Our asymptotic analysis reveals that the value process, adjusted for the derived slant asymptote, adheres to a stationary distribution. By capitalizing on price deviations and value trends, the strategy profits by longing undervalued or shorting overvalued processes based on their respective upward or downward slopes. Positions are strategically closed when they revert to the asymptote, thus securing profits and avoiding counterproductive trades against prevailing trends. In this context, conventional stationary-based PTS can be considered a specific instance of our broader approach when the asymptote is non-trended. To refine trade selection, we evaluate the mean-reversion velocity, monitoring the frequency at which the portfolio's value crosses the slant asymptote to exclude high-risk pairs. Empirical evidence underscores our method's superiority over conventional stationary PTS, delivering higher average returns per trade, improved Sharpe ratios, and increased trading opportunities, even amidst the financial uncertainties of the COVID era. [ABSTRACT FROM AUTHOR]

In literature, color words serve as important carriers for writers to convey their emotions. In this paper, color words in literary works written by over 30 famous writers from different countries and regions in world literature are selected as the research object. According to the frequency of their use in the selected literary works, our analysis divides the different color symbols into two types: high-frequency and low-frequency. Among the various color symbols, red, blue, white, black, and yellow are classified as high-frequency color symbols. Purple, gray, green, and brown belong to low-frequency color symbols. Comparatively speaking, the metaphorical meanings of high-frequency color symbols are richer and more diverse, while the symbolic meanings of low-frequency color symbols are relatively simple. Through the analysis of the color symbols in the literary works, we find that there is a benign interaction between color symbols and literary works. On the one hand, writers convey their pursuit of art and aesthetics through color symbols. Color symbols become a perfect medium for them to express ideas, show themes, and construct characters. On the other hand, literary works also expand and enrich the metaphorical meaning of color symbols. [ABSTRACT FROM AUTHOR]

By studying the differences between futures prices and exchange‐traded fund prices for the S&P 500 index, original results are obtained about the distribution and persistence of the microstructure noise component created by positive bid‐ask spreads and discrete price scales. The bivariate density of this component for futures and exchange‐traded fund prices is estimated from high‐frequency prices, to provide estimates of the marginal noise densities and measures of noise dependence across the markets studied. Properties of the residual microstructure noise, created by factors other than discrete prices, are also estimated. The residual component has more variation and less persistence than the discrete‐price component during the period examined, from January 2010 to December 2012. [ABSTRACT FROM AUTHOR]

This study investigates the magnetic response of Ho3+ doped Ni 0.4 Cu 0.6 Ho y Fe 2-y O 4 (y = 0.0, 0.02, 0.04, 0.06, and 0.08) spinel ferrites (SFs) and their correlation with crystallite size. The synthesis was achieved using a sol-gel auto-combustion (SGAC) route and performed different characterizations, including X-ray diffraction (XRD), Scanning electron microscope (SEM), Energy dispersive x-ray (EDX), Inductively coupled plasma atomic emission spectroscopy (ICP-AES), and vibrating sample magnetometer (VSM) analysis. The cubic spinel phase was verified via XRD in pure NCF and Ho3+ doped NCF samples. The lattice constant (a) was improved from 8.344 Å to 8.378 Å. The substitution of Ho3+ ions led to a decrease in porosity from 42.22 % to 39.54 %. The introduction of Ho3+ ions also reduced the crystallite size (D) from 37.05 nm to 27.72 nm. The specific surface area (S) was increased from 27.44 g/cm2 to 36.14 g/cm2 with the doping of Ho3+. The average particle size (D S) was decreased from 54 nm to 35 nm. The EDX and ICP-AES analyses confirmed the good agreement with the theoretical composition. The VSM measurements provided insights into their magnetic properties. Furthermore, the doping of Ho3+ ions enhanced coercivity (H C), while reducing saturation magnetization (M S) from 64.35 emu/g to 16.22 emu/g. The decrease in crystalline anisotropy (K) observed at higher concentrations of Ho3+ may result from the increase in coercivity, potentially attributable to the smaller crystallite size of the single-domain SFs particles. The single-phase matrix and their magnetic behaviour showed that the Ho3+ doped Ni–Cu SFs samples are suitable for high-frequency applications. [Display omitted] • Ni 0.4 Cu 0.6 Ho y Fe 2-y O 4 was prepared via the sol-gel auto-combustion technique. • The crystallite size was the minimum (27.72 nm) for the y = 0.08 (NCHF4) sample. • The sample has y = 0.08 (NCHF4) and contains maximum coercivity (1031.44 Oe). • The sample has y = 0.08 (NCHF4) and is best-suitable for high-frequency applications. [ABSTRACT FROM AUTHOR]

With the demand for the miniaturization and integration of wireless power transfer (WPT) systems, higher frequency is gradually becoming the trend; thus, the power electronic device has become one of the main reasons for limiting the development. Therefore, further research on high-frequency inverters and purposeful design according to the characteristics of WPT systems are of great significance to promote the development of high-frequency WPT technology. There is still no literature that summarizes all the inverter circuits that can be applied to WPT systems, which makes it extremely difficult to find an inverter that meets the designer's requirements. This paper reviews the high-frequency inverters for WPT systems, summarizes the derived topologies based on power amplifiers and H-bridge inverters, investigates the main factors restricting the development of high-frequency inverters, and analyzes the research directions for future development. [ABSTRACT FROM AUTHOR]

The multifunctionality feature of graphene field-effect transistors (GFETs) is exploited here to design circuit building blocks of high-data-rate modulators by using a physics-based compact model. Educated device performance projections are obtained with the experimentally calibrated model and used to choose an appropriate improved feasible GFET for these applications. Phase-shift and frequency-shift keying (PSK and FSK) modulation schemes are obtained with 0.6   G Hz GFET-based multifunctional circuits used alternatively in different operation modes: inverting and in-phase amplification and frequency multiplication. An adequate baseband signal applied to the transistors' input also serves to enhance the device and circuit performance reproducibility since the impact of traps is diminished. Quadrature PSK is also achieved by combining two GFET-based multifunctional circuits. This device circuit co-design proposal intends to boost the heterogeneous implementation of graphene devices with incumbent technologies into a single chip: the baseband pulses can be generated with CMOS technology as a front end of line and the multifunctional GFET-based circuits as a back end of line. [ABSTRACT FROM AUTHOR]

In 2020, Colorado experienced the most severe wildfire season in recorded history, with wildfires burning 625 357 acres across the state. Two of the largest fires burned parts of Rocky Mountain National Park (RMNP), and a study was initiated to address concerns about potential effects on drinking water quality from mobilization of ash and sediment. The study took advantage of a wealth of pre‐fire data from adjacent burned and unburned basins in western RMNP. Pre‐ and post‐fire data collection included discrete sample collection and high‐frequency water‐quality measurements using in‐stream sensors. Kruskal–Wallis tests on discrete data indicated that specific conductance, base cations, sulphate, chloride, nitrate, and total dissolved nitrogen concentrations increased post‐fire, whereas silica and dissolved organic carbon (DOC) did not (p ≤ 0.05). In‐stream sensors captured large spikes in concentrations of nutrients, turbidity, and DOC in the burned basin that were missed by discrete sampling. Sensor data indicated nitrate and turbidity increased by up to one and two orders of magnitude, respectively, from pre‐event concentrations during storms, and DOC increased up to 3.5×. Empirical regression equations were developed using pre‐fire data and applied to the post‐fire period to estimate expected stream chemistry in the absence of fire (a 'no‐fire' scenario). Overlays of actual post‐fire chemistry showed the timing and magnitude of differences between observed and 'estimated' chemistry. For most solutes, observed post‐fire concentrations were notably greater than expected under the 'no‐fire' scenario, and differences were greatest during storm events. Comparison of data from the burned and unburned basins indicated DOC concentrations were affected by climate as well as fire. Results from this study demonstrate the importance of both pre‐fire data and high‐frequency data for characterizing dynamic hydrochemical responses in wildfire‐affected areas. [ABSTRACT FROM AUTHOR]

The aim of this paper is to develop a forecasting method with global interval input and output for interval-valued financial time series by combining the VAR(p) process, the volatility information and neural network, namely VAR-NN. To reflect the volatility information, four types of interval-valued data volatility information from both the relative and absolute perspectives are constructed. Furthermore, the neural network is combined to produce the parameters. The developed forecasting model is finally applied to the highest and lowest hourly prices of the Shanghai Composite Index prediction. Numerical study shows the feasibility and validity of the developed improved VAR model. [ABSTRACT FROM AUTHOR]

This paper presents simulation analysis of an inverter made from non-aligned double gate field effect transistors (NADGFETs) in Sub-100 nm regime. The inverter consists of n-channel NADGFET and p-channel NADGFET device with a channel length of 40 nm and 50% non-alignment between gate and source/drain. The response of the inverter was tested by a combination of gate dielectric constant (k) and metal work function (ϕ). Three gate dielectrics namely, SiO2 (k = 3.9), Si3N4 (k = 7.2), HfO2 (k = 24), and three metal work function namely tungsten (ϕ = 4.5 eV), molybdenum (ϕ = 4.75 eV), gold (ϕ = 5 eV), were considered in the NADGFET inverter. This paper defines a kϕ index as characterising parameter to explore the best response from inverter configuration with minimum propagation delay, and minimum power consumption at super-high frequency. The paper proposes to analyse the NADGNFET device, in term of ION current, ION/IOFF ratio, cut-off frequency, and gate delay. And observes that low k material with moderate metal work function gives best response. The work then simulates the inverter and group the results into voltage transfer curve (VTC), transient response, and power dissipation category. The result shows that when inverter was subjected to high frequency, all the kϕ combination responds good, however when the inverter was subjected to super-high frequency, the low value of kϕ combination performs well. Thus, the result concludes that SiO2-M2 combination will be best selection to get minimum propagation delay and dynamic power dissipation by the inverter. The test strategy presented in this paper on the basis of kϕ index can serve as benchmark to test inverter device at super-high frequency. [ABSTRACT FROM AUTHOR]

Hypoxia in coastal waters is a pressing ecological problem caused by continued eutrophication and climatic change that has widespread consequences for metazoan life and biogeochemical cycles. Numerous studies have investigated the controls on seasonal hypoxia formation and persistence in many of the world's large estuaries and coastal hypoxic zones, but far fewer studies have examined the controls on short-term oxygen variability that leads to diel-cycling hypoxia in shallow-water environments. We utilized a unique, comprehensive (181 stations) record of dissolved oxygen concentrations collected at shallow water sites (primarily < 2 m) at high frequency (15 min) throughout the estuarine complex of the Chesapeake Bay and its tributaries to quantify how internal and external variables co-varied with dissolved oxygen. We used a combination of time-series analysis, harmonic analysis, and machine learning (e.g., classification and regression trees (CART)) approaches to identify spatial patterns in major controls on oxygen variability and the duration of moderate hypoxia. We found that key controls on oxygen variability varied substantially over space. For example, photosynthetically active radiation (PAR) was a strong predictor of oxygen dynamics in the majority of mesohaline waters. In more fetch-exposed stations, wind strongly controlled hypoxic duration, but in eutrophic, inshore locations, chlorophyll a, or turbidity were often better predictors. Specifically, diel oxygen variability was muted in upstream regions characterized by high turbidity. The duration of low oxygen conditions, which we defined conservatively as less than 4.8 mg O2 L−1 (156 µM), was strongly controlled by temperature, and simple projections of regional warming and CART-derived oxygen thresholds suggest that the Bay could experience a 10% increase in this type of hypoxia duration by mid-to-late twenty-first century. The ratio of tidal to biological variability in oxygen was found to increase under conditions of higher turbidity, stronger wind, and lower salinity, but biological variability was typically a factor of two higher than tidal variability. Although chlorophyll-a generated high oxygen concentrations at some locations, those stations with exceptionally high chlorophyll a (> 30 µg L−1) were the most vulnerable to hypoxia. Because conventional water quality modeling frameworks are designed to capture hypoxia on relatively long time scales, these new insights can help inform updated oxygen models to support the management of shallow-water estuaries in the face of managed nutrient reductions and climate change. [ABSTRACT FROM AUTHOR]

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Introduction: The principle of passive sound control is based on the phenomenon of sound absorption by absorbers. The factors affecting sound absorption include porosity, pore size, pore opening size, thickness, and air flow resistance. Materials and Methods: In this study, the authors compared the optimization results of the effective parameters on sound absorption coefficient (AC) using the three optimization methods: Guided Local Search (GLS), Genetic Algorithm (GA) and Particle Swarm Optimization (PSO). The programming was done in MATLAB software. Thicknesses of 5, 10, 20, 30 and 40 mm were chosen for optimization at frequencies of 500 to 3000 Hz. Results: In frequencies above 2 kHz (thickness 5 to 40 mm), the three optimal methods had the same performance and estimated AC of 1. At low frequencies of 2 kHz and thicknesses of 30 and 40 mm, GA and PSO methods obtained an AC of 1. Conclusion: It seems that the GA and PSO optimization algorithm are suitable methods to optimize the AC of metal foam in low and high frequencies.

High-frequency water quality measurements in streams and rivers have expanded in scope and sophistication during the last two decades. Existing technology allows in situ automated measurements of water quality constituents, including both solutes and particulates, at unprecedented frequencies from seconds to subdaily sampling intervals. This detailed chemical information can be combined with measurements of hydrological and biogeochemical processes, bringing new insights into the sources, transport pathways, and transformation processes of solutes and particulates in complex catchments and along the aquatic continuum. Here, we summarize established and emerging high-frequency water quality technologies, outline key high-frequency hydrochemical data sets, and review scientific advances in key focus areas enabled by the rapid development of high-frequency water quality measurements in streams and rivers. Finally, we discuss future directions and challenges for using high-frequency water quality measurements to bridge scientific and management gaps by promoting a holistic understanding of freshwater systems and catchment status, health, and function.

1. The Kaijiang duck is a native Chinese breed known for its excellent egg laying performance, killing-out percentage (88.57%), and disease resistance. The assessment of population genetic structure is the basis for understanding the genetics of indigenous breeds and for their protection and management. 2. In this study, whole-genome sequencing was performed on 60 Kaijiang ducks to identify genetic variations and investigate the population structure. Homozygosity (ROH) analysis was conducted to assess inbreeding levels in the population. 3. The study revealed a moderate level of inbreeding, indicated by an average inbreeding coefficient of 0.1043. This may impact the overall genetic diversity. 4. Genomic Regions of Interest identified included 168 genomic regions exhibiting high levels of autozygosity. These regions were associated with processes including muscle growth, pigmentation, neuromodulation, and growth and reproduction. 5. The significance of these pathways indicated their potential role in shaping the desirable traits of the Kaijiang duck. These findings provide insights into the genetic basis of the Kaijiang duck's desirable traits and can inform future breeding and conservation efforts. [ABSTRACT FROM AUTHOR]

The expanding realm of high‐frequency electronics necessitates materials with exceptional attributes: notably, a low dielectric constant (Dk) to minimize signal propagation delays, high thermal conductivity for effective heat dissipation, higher breakdown strength, and robust mechanical properties to withstand demanding operational environments. While cycloolefin copolymers (COC) excel in electrical insulation, chemical resistance, and mechanical durability, their intrinsic slightly higher dielectric constant compared to other polymers, along with challenges such as poor dispersibility and low compatibility with nanoparticles, hinder their full potential in this domain. Considering these drawbacks, this study fabricated a series of COC/mica composites by integrating natural mica particles into the COC matrix via a CTAB‐assisted surface modification of mica to enhance dispersibility and mitigating particle aggregation through in‐situ mixing and hot‐press methods. The resultant composites demonstrate an outstanding ultra‐low Dk of 1.44, marking a significant decrease of over 36% compared to pristine COC with a Dk of 2.26, along with exceptionally low dielectric loss (δ) of 0.00013 at the frequency of 10 GHz, high dielectric breakdown strength ~49.40 kV/mm and enhanced thermal conductivity up to 0.88 W/(m K) at 40% mica loading. Additionally, the composites heightened mechanical performances like tensile strength 69 MPa at 6.5% elongation at break, impact strength up to ~17.9 kJ × m−2, and exceptional water resistance with absorption below 0.097%. These exceptional ultra‐low dielectric performance with above mentioned properties can meet the stringent requirements of modern high‐frequency electronics packaging for next generation electronics development. Highlights: Surface modification by CTAB enhanced homogeneous dispersibility of composites.Achieved ultra‐low dielectric constant and loss compared to pure COC.Thermal conductivity improved significantly with incorporation of mica.Unlocking high‐frequency applications potential with ultralow Dk performance. [ABSTRACT FROM AUTHOR]

We propose a novel variant of the Localized Orthogonal Decomposition (LOD) method for addressing time-harmonic scattering problems of Helmholtz type with high wavenumber k. This method operates on a coarse mesh of width HH and identifies local finite element source terms that produce rapidly decaying responses under the solution operator. These source terms can be constructed with high accuracy from independent local snapshot solutions on patches of width ℓH, and they are used as problem-adapted basis functions. Compared to classical LOD and other state-of-the-art multiscale methods, our approach demonstrates that the localization error decays super-exponentially as the oversampling parameter ℓ increases. This indicates that optimal convergence is achieved under a substantially relaxed oversampling condition of ℓ≳(log⁡κ/H)(d−1)/d, where d represents the spatial dimension. Numerical experiments highlight the significant improvements in both offline and online performance of the method, even in the presence of heterogeneous media and perfectly matched layers. [ABSTRACT FROM AUTHOR]

The development of chemical sensor devices operating in non-contact mode is of primary interest due to the demand from various industries for a fast, simple and inexpensive determination of chemical composition in different media in a non-invasive way. One of the promising directions for the development of analytical devices with such characteristics is the use of high-frequency electrical signals. The paper discusses the evolution of high-frequency contactless conductometry method, likewise other methods and devices operating on similar physical principles (dielectric spectroscopy, microwave sensors, C4D detectors). [ABSTRACT FROM AUTHOR]

This research paper focuses on the application of fuzzy logic control in the high-frequency switching control of SEPIC DC/DC converters and three-phase inverters for photovoltaic systems. The research is separated into two distinct sections. The first part entails the design and development of a prototype mechanism for a single-ended primary-inductor converter (SEPIC), which is utilized to manage the input voltage from the PV system. The operation of this SEPIC DC/DC converter incorporates real-time fuzzy logic control principles and methods. The second part involves the design and creation of a three-phase inverter mechanism (SVPWM) responsible for driving a three-phase induction motor. In a similar manner, fuzzy logic control principles and methods are independently employed for the operation control of this three-phase inverter. Both control mechanisms are integrated with the mathematical model of MATLAB/Simulink program and synchronized with the TMS320F28379D microcontroller in order to effectively regulate their respective functions. The evaluation and experimentation of the developed mechanisms demonstrate the successful regulation of input and output voltages for the SEPIC DC/DC Converter, as well as the efficient control of the three-phase induction motor's speed, torque, and power using the three-phase inverter. [ABSTRACT FROM AUTHOR]

Targeting reservoirs below seismic resolution presents a major challenge in reservoir characterization. High-resolution seismic data is critical for imaging the thin gas-bearing Khadro sand facies in several fields within the Lower Indus Basin (LIB). To truly characterize thin beds below tuning thickness, we showcase an optimally developed deep learning technique that can save up to 75% turn-around time while significantly reducing cost. Our workflow generates high-frequency acoustic impedance synthetics by utilizing a deep neural network (DNN) at the reservoir level vis-a-vis validating the results with existing geological facies. Simultaneously, we introduce continuous wavelet transform (CWT); wherein the three components (real, imaginary, and magnitude) are interrelated to obtain a resultant high-frequency seismic volume. A strong agreement is established at available wells to achieve a higher resolution seismic by injecting higher frequencies, which is then populated throughout the 3D cube. An excellent correlation is met with key seismic attributes extracted across the field for original and CWT-based synthetic seismic. The augmented seismic volume with enhanced frequency range substantiates the dominant frequency (Fd) and resolves thin beds, which is also validated with the help of wedge modeling of both acquired and high-frequency datasets. As a geologically valid solution, our approach effectively resolves an initially 54 m bed to ∼25 m. This deep-learning methodology is ideally suited to regions where the acquired seismic has limited resolution and lacks advanced reservoir characterization.

In the absence of high-frequency visual observation, low-resolution (LR) targets (e.g., objects, human body keypoints) are intrinsically difficult to detect in unconstrained images. This challenge can be further exasperated by typical downsampling operations (e.g., pooling, stride) of existing deep networks (e.g., CNNs). To tackle this challenge, in this work, we introduce a generic, High-Frequency Information Preservation (HFIP) block as a replacement for existing downsampling operations. It is composed of two key components: (1) the decoupled high-frequency learning component, which extracts the high-frequency information along the vertical and horizontal directions separately, and (2) the dilated frequency-aware channel correlation component, which decomposes the input feature map into multiple smaller ones in a dilated manner, concatenates them by channel, and then correlates the combined channels in the frequency space. Our module can generally be integrated into existing network architectures for target detection (e.g., YOLO, HRNet). Extensive experiments on low-resolution human pose estimation and object detection tasks show that our HFIP technique can generally boost the performance of state-of-the-art detection models significantly, e.g., improving the object detection accuracy of YOLOv5s by an absolute margin of 3.30% in mAP under a resolution of 640 × 640 compared to the COCO benchmark.

The 2016 Mw 6.8 Chauk, Myanmar earthquake was one of the largest earthquakes in Myanmar, leading to significant damage to historical monuments and the first earthquake to occur in the instrumental era. In the current study, broadband (0.01–25 Hz) ground motions are simulated in the 4.5° × 4.5° region around the epicenter to investigate the ground-motion characteristics of the event. Towards this goal, deterministically generated low-frequency and stochastically simulated high-frequency ground motions are combined to create three-component broadband seismograms. The simulated ground motions are further compared with the available strong motion data recorded in the near-field and far-field stations. Thus, the efficacy in modeling the ground motions is quantified through the estimation of the goodness of fit between the 5% damped acceleration response spectra obtained from recorded and simulated ground motions. Furthermore, the peak ground acceleration (PGA) of the simulated ground motions for the entire region is presented in the form of a contour map along with its spatial variation with the region's topography. The simulated PGA is further compared with the global ground motion models developed for subduction zone intraslab earthquakes. Most importantly, acceleration time histories are generated at the locations of severely damaged monuments in Bagan and Nyuang-U city, which can further be utilized for nonlinear dynamic analysis of the structures. [ABSTRACT FROM AUTHOR]