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This work focuses on optimizing the estimation of accumulated rain from measurements of the attenuation level of signals from commercial microwave links (CMLs). The process of accumulated rain estimation is usually based on estimation after detection, where it is first determined whether there is rain for a specific period, and then the accumulated rain at the detected rainy period is estimated. Naturally, errors in detection affect the accuracy of the consequent accumulated rain estimation. Traditionally, the detection and the estimation steps are designed independently. The detection threshold is arbitrarily set at the lowest level that would be declared as rain, without considering its effect on the accuracy of the accumulated rain estimation. This study applies a novel method that sets a detection threshold to optimize estimation after detection and apply it for accumulated rain estimation. It is based on optimizing a postdetection estimation risk function that incorporates both the estimation and detection-related errors; this essentially takes into consideration the coupling of the detection and the estimation stages and thus optimizes the overall accumulated rainfall estimation. The proposed approach is applied to actual CML attenuation measurements taken from a cellular network in Gothenburg, Sweden. This demonstrates that the proposed method achieves better accuracy for accumulated rain estimation compared with the detection threshold being set independently. [ABSTRACT FROM AUTHOR]

AbstractGiven M≥2 distributions defined on a general measurable space, we introduce a nonparametric (kernel) measure of multi-sample dissimilarity (KMD)—a parameter that quantifies the difference between the M distributions. The population KMD, which takes values between 0 and 1, is 0 if and only if all the M distributions are the same, and 1 if and only if all the distributions are mutually singular. Moreover, KMD possesses many properties commonly associated with f-divergences such as the data processing inequality and invariance under bijective transformations. The sample estimate of KMD, based on independent observations from the M distributions, can be computed in near linear time (up to logarithmic factors) using k-nearest neighbor graphs (for k≥1 fixed). We develop an easily implementable test for the equality of M distributions based on the sample KMD that is consistent against all alternatives where at least two distributions are not equal. We prove central limit theorems for the sample KMD, and provide a complete characterization of the asymptotic power of the test, as well as its detection threshold. The usefulness of our measure is demonstrated via real and synthetic data examples; our method is also implemented in an R package. Supplementary materials for this article are available online. [ABSTRACT FROM AUTHOR]

Summary: In this manuscript, a novel energy detection‐based chaotic whale optimization algorithm (ED‐CWOA) is proposed to maximize the spectrum utilization, duration, and threshold in cognitive radio network (CRN). Here, the spectrum utilization is designed taking into account sensing duration and threshold in multi‐objective function is formulated by considering its primary user (PU) protection restrictions and secondary user (SU) throughput. To get the global optimal solution, the CWOA and the multi‐objective optimization problem are finally carried out on a single objective. The execution is performed on NS2 simulator. The simulation outcome demonstrates that the proposed ED‐CWOA system has lower delay 33.878%, 26.206%; higher delivery ratio 35.536%, 22.65%; lower Fairness Index 46.66%, 58.332%; lower energy consumption 25.462%, 35.524%; and higher throughput 96.82%, 49.28% for different nodes analyzed with the existing methods, like energy detection‐based bivariate Levy‐stable bat algorithm (ED‐BLSBA) and genetic algorithm‐based energy detection (ED‐GA), respectively. The simulation outcome indicates that the proposed system may be able to get the optimal global solutions efficiently and accurately. [ABSTRACT FROM AUTHOR]

Background Taste sensitivity has been reported to influence children’s eating behaviour and contribute to their food preferences and intake. This study aimed to investigate the associations between taste sensitivity, eating behaviour, food frequency and BMI (Body Mass Index) in preadolescents. Methods Preadolescents’ taste sensitivity was measured by detection threshold of sweetness (sucrose), sourness (citric acid), saltiness (sodium chloride), bitterness (caffeine, quinine), and umami (monosodium glutamate). In addition, the Child Eating Behaviour Questionnaire (CEBQ), the Food Propensity Questionnaire (FPQ) measuring food frequency, and the children’s body weight and height were completed by the parents. A total of 69 child-parent dyads participated (preadolescents mean age =10.9 years). Results Taste sensitivity to caffeine bitterness was significantly associated with eating behaviour in food responsiveness, emotional overeating, and desire to drink. The preadolescents who were less sensitive to caffeine bitterness had higher food responsiveness scores. Those who were less sensitive to caffeine bitterness and to sweetness had higher emotional overeating scores. In addition, preadolescents who were less sensitive to sourness and bitterness of both caffeine and quinine demonstrated to have higher scores in desire to drink. There was no association between taste sensitivity and FPQ, but significant differences were observed across preadolescents’ BMI for FPQ of dairy food items, indicating higher consumption of low-fat milk in the overweight/obese compared to the underweight/normal-weight subjects. There was no significant difference in taste sensitivity according to BMI. Preadolescents’ eating behaviour differed across BMI, demonstrating a positive association between BMI and food approach, and a negative association between BMI and food avoidance. Conclusions This study contributes to the preliminary understanding of the relationships between taste sensitivity and eating behaviour in preadolescents. The results may be used to develop effective strategies to promote healthy eating practices by considering taste sensitivity in preadolescents.

This work focuses on optimizing the estimation of accumulated rain from measurements of the attenuation level of signals from commercial microwave links (CMLs). The process of accumulated rain estimation is usually based on estimation after detection, where it is first determined whether there is rain for a specific period, and then the accumulated rain at the detected rainy period is estimated. Naturally, errors in detection affect the accuracy of the consequent accumulated rain estimation. Traditionally, the detection and the estimation steps are designed independently. The detection threshold is arbitrarily set at the lowest level that would be declared as rain, without considering its effect on the accuracy of the accumulated rain estimation. This study applies a novel method that sets a detection threshold to optimize estimation after detection and apply it for accumulated rain estimation. It is based on optimizing a post-detection estimation risk function that incorporates both the estimation and detection-related errors; this essentially takes into consideration the coupling of the detection and the estimation stages and thus optimizes the overall accumulated rainfall estimation. The proposed approach is applied to actual CML attenuation measurements taken from a cellular network in Gothenburg, Sweden. This demonstrates that the proposed method achieves better accuracy for accumulated rain estimation compared with the detection threshold being set independently.

Unmasked behavioral audiograms of two California sea lions (Zalophus californianus), an adult female (F01) and a subadult male (M02), were recorded using narrow-band frequency-modulated hearing test signals. Signals had a duration of 1 s and center frequencies ranging from 0.031 to 80 kHz. Hearing thresholds were measured by varying test signal amplitude according to the updown staircase method. The resulting underwater audiograms (50% detection thresholds) of the two sea lions were similar and showed the typical mammalian U-shape. Maximum hearing sensitivity (58 and 57 dB re 1 µPa) occurred at 11.3 kHz for F01 and at 8 kHz for M02, respectively. The range of best hearing (defined as < 10 dB from the maximum sensitivity) was from 1 to 16 kHz (four octaves). The detection thresholds for hearing test signal frequencies 0.031, 0.040, and 0.050 kHz were lower than expected, possibly caused by a shift in perceptional modality from auditory to vibrotactile, or due to the difficulty in measuring accurate SPLs of such low frequencies in a pool. Measurements of particle motion deemed detection of these very low frequencies via the vibrissae unlikely. The present study extends the frequency range for which the hearing of California sea lions has been tested. Based on the two audiograms of the present study and audiograms reported by Reichmuth et al. (2013) and Cunningham & Reichmuth (2016), a revised generic audiogram for California sea lions is proposed. [ABSTRACT FROM AUTHOR]

Fatigue crack propagation can considerably reduce the life of components, leading to sudden failures. This paper provides a method for fatigue life prediction based on ultrasonic non-destructive inspection applied on Al 2024 T3 material.A new crack quantification model based on ultrasonic waves features is developed. To analyse the performance and efficacity of the model, the probability of detection is determined using the “signal response” technique.The Paris model is used to predict the fatigue life taking into consideration the initial crack distributions, the dispersion of the parameters underlined by the Least-squares method and Monte-Carlo simulations.Reliability evaluation is discussed later for two cases: Detection and No-detection case.If no indication is presented, an inspection detection threshold is determined and optimized. This proposed indicator will be helpful for industrial environments whenever the inspection machine does not have any indication.Considering the ultrasonic inspection data, an updating reliability via the Bayesian approach is suggested. The results of this approach can lead to a gain in the life span or a gain of the costs generated by the failure of the part.

This study used a hydrothermal approach to synthesis carbon dots (CDs) from apricot peel, which were then used as a probe for the selective and sensitive detection of Cd ^2+ ions. The synthesized CDs’ surface groupings, structure, shape, biological nature, and overall size were examined using standard characterization techniques. With a quantum yield of 22.1%, these CDs showed excitation-dependent fluorescence emission. In addition, Cd ^2+ ions were distinguished from other metal ions by a noticeable drop in fluorescence intensity. The fluorescence probe showed a linear response ranging from 0–300 μM and a detection threshold (DT) of 0.21 μM, indicating its effectiveness for Cd ^2+ detection. Furthermore, the CDs demonstrated the practical application by detecting Cd ^2+ ion in actual water samples.

In this study, the spherical particle model and ten nonspherical particle models describing the scattering properties of snow are evaluated for potential use in precipitation estimation from spaceborne dual-frequency precipitation radar. The single scattering properties of nonspherical snow particles are computed using discrete dipole approximation (DDA), while those of spherical particles are determined using Mie theory. The precipitation profiles from WRF output are then input to a forward radiative transfer model to simulate the radar reflectivity at Ka-band and Ku-band. The results are validated with Global Precipitation Mission Dual-Frequency Precipitation Radar measurements. Greater consistency between the simulated and observed reflectivity is obtained when using the sector- and dendrite-shape assumptions. For the case in this study, when using the spherical-shape assumption, radar underestimates the error of the cloud's top by about 300 m and underestimates the error of the cloud's area by about 15%. As snowflake shapes change with temperature, we use the range between −40 °C and −5 °C to define three temperature layers. The relationships between reflectivity (Z) and precipitation rate (R) are fitted separately for the three layers, resulting in  Z = 134.59 · R 1.184  (sector) and  Z = 127.35 · R 1.221  (dendrite) below −40 °C. [ABSTRACT FROM AUTHOR]

Introduction: Mizaj-e-Advia (Temperament of drug) is the central concept for drug action in traditional Unani medicine. Mizaj-e-Advia is determined by different methods, of them Qiyas (Analogy) and Tajriba (Experimentation) are the conventional one. Tajriba is applied to confirm the Mizaj-e-Advia of drugs and Qiyas is undertaken by comparison of different physico-chemical properties of drug substances with a known comparator drug. Organoleptic characters i.e.colour, taste, smell, weight, texture, etc., are the most important determinants to predict Mizaj-e-Advia in humans. Taste is considered as one of the strongest determinant in assessment of Mizaj-e-Advia. Since, they are very subjective indicators, so there is a need to assess them with an objective technique. The present study attempted to evaluate the relative saltiness of drugs with salty taste. Methodology: The taste of different salty drugs in relation to standard as prescribed in Unani system of Medicine i.e., Namak Ta'am (Sodium chloride, NaCl) was assessed by serial dilution method. The value has been expressed as a ratio with respect to NaCl. The Darjate-Mizaj (grades of temperament) of various salt tasting drugs was recorded from classical Unani literature and their correlation coefficient was calculated. Results: A positive moderate correlation was observed between the Darjat-e-Mizaj and the saltiness values of various drugs of salt taste. The observation from the data employed that there was variation in salt detection limit among various salt tasting drugs. Naushadar (Ammonium Chloride) was observed to have greater tendency to retain its saltiness value, and Namak-e-Sanbhar (Impure Sodium Chloride) was observed to have least saltiness value among the various salt tasting drugs. [ABSTRACT FROM AUTHOR]

Due to the population growth in metropolitan regions such as Tehran and the existence of the underground constructions, the importance of seismic investigation is evident to reduce damages caused by probable earthquakes. Accordingly, the precise detection of micro to medium earthquakes is effective tool for tracking fault dynamics in seismic cycles, as well as for earthquake prediction and seismic hazard assessment. In this study, the recorded ambient noise at Tehran Disaster Mitigation and Management Organization (TDMMO) as well as Road, Housing and Urban Development Research Center (BHRC) networks as an accelerometer network installed in Tehran city, have been used on the point of characterizing the noise spectrum for each station as a function of time for obtaining the detection threshold of these networks. Therefore, an indirect approach based on the signal-to-noise ratio (SNR) in the time domain, with parameterization in the frequency domain is applied. Based on SNR method, the source signature is simulated by a simple source model called a circular fault model. Thus, the signal is estimated via the Brune function as most common models for circular faults. While, to determine the noise, the real data of 13 accelerometer stations of the TDMMO and seven joint stations with the BHRC are used. In this respect, the Power Spectral Density (PSD) of noise is calculated using PQLX software in the frequency domain and then is transferred to the time domain by the Parsville theorem. Eventually, the SNR value is acquired for each station by dividing these two quantities. As a result, the minimum detectable magnitude in at least five stations with an SNR larger than 5 is 3.0 for Swaves and 3.3 for P-waves, which frequently occurs in the center of the network. Another finding of these studies is to analyze the effect of spatial variations of the noise on the detection ability. For this, a constant noise is allotted to all stations, lowest observed noise level, as a result of which, the smallest magnitude detectable is 1.7 for S-waves and 2.2 for P-waves. At last, the sensitivity of the detection capability to three fundamental parameters, including stress drop, focal depth and reduced time, which are assumed as constant values within the network, are investigated. In fact, these parameters are strongly affected by uncertainty and are not absolute values. Consequently, the impact of their changes was studied. In our case, it is implied that the variation in the stress drop has no effect on the detection threshold, but the focal depth and the reduced time are effectual. A 15 km variation in the focal depth, the detectable magnitude changes by 0.3 units, and by changing the reduced time from 0.015 s to 0.035 s, the detectable magnitude varies by 0.4 units in Mw. [ABSTRACT FROM AUTHOR]

In order to solve the problem of low operating efficiency caused by environmental constraints in virtual reality interaction(Virtual Reality Interaction, VRI), a fixed offset detection threshold estimation method based on hand remapping in virtual reality is proposed to improve the operating efficiency of using hands. This method started from people’s psychological perception and introduces a psychometric function to calculate the offset detection threshold to improve the interactive experience. Specifically, it first designed an experiment according to the Two Alternative Forced Choice(2 AFC) theory, and the differences in the subjects’ sensations in the process of completing the target grasping task using different offset virtual hands were recorded as the evaluation criteria, while the subjects completed the task of time were also recorded. According to the psychometric function(Quickpsy) calculated the sensory difference, and the detection threshold of the remapping interaction is estimated. Then, covariance determine the significant factors affecting the performance of the touch task, the threshold judge the direction, amplitude, axial direction and their interaction, if within the threshold range, the above factors no longer affected the performance of the task. Finally, the feasibility of the proposed method is demonstrated through a VR(Virtual Reality) hospital material intelligent distribution system. The research results showed that the appropriate offset shortens the time for the user to complete the touch task. It improved the interaction efficiency while reduced the impact of the traditional offset calculation method on the VR interaction fidelity. [ABSTRACT FROM AUTHOR]

Purpose: Early warning in the travel origins is crucial to prevent disease spreading. When travel origins have delays in reporting disease outbreaks, the exported cases could be used to estimate the epidemic.Methods: We developed a Bayesian model to jointly estimate the epidemic prevalence and detection delay using the exported cases and their arrival and detection dates. We used simulation studies to discuss potential biases generated by the exported cases. We proposed a hypothesis testing framework to determine the epidemic severity.Results: We applied the method to the early phase of the COVID-19 epidemic of Wuhan, United States, Italy, and Iran and found that the indicators estimated from the exported cases were consistent with the domestic data under certain scenarios. The exported cases could generate various biases if not modeled properly. We presented the required number of exported cases for determining different severity levels of the outbreak.Conclusions: The exported case data is a good addition to the domestic data but also has its drawbacks. Utilizing the diagnosis resources from all countries, we advocate that countries work collaboratively to strengthen the global infectious disease surveillance system. [ABSTRACT FROM AUTHOR]

Under low-frequency background noise environments, due to the characteristics of poor stability and many interference targets of noise, the detection of unknown low-frequency sonar signals faces huge challenge. And sonar pulse signal detection methods based on time domain or frequency domain have the limitation of insufficient detection Signal-to-Noise Ratio (SNR). In order to improve the detection capability of weak sonar pulse signal in low frequency background noise environments, a Detection method based on normalized short-time Fourier transform-Radon transform for Low frequency Sonar pulse signal (DNLS) is proposed, which is a constant false alarm detection method in normalized short-time Fourier transform-Radon transform domain. In DNLS method, after the normalized short-time Fourier transform-Radon transformation, low-frequency noise energy to be dispersed into the entire transformation domain, and the sonar pulse signal energy containing the Linear Frequency Modulation (LFM) component is concentrated at a specific target point in the normalized short-time Fourier transform-Radon transform transformation domain, which can obtain a higher local SNR than the time-domain SNR. Moreover, the specific target point is distinguishable from the background noise, and the impulse signal detection decision is completed by constructing hypothesis test statistics on the target point data. The DNLS method solves the detection problems of low-frequency background such as poor stability, large fluctuations, and more interference. And the method of obtaining the test statistics of the constant false alarm detection, estimating the background noise and calculating the detection threshold is given. Extensive simulation results and actual data processing show that, under the simulation condition, in the minimum detection SNR of LFM, Continuous Wave(CW)-LFM and pulse trains of frequency modulated pulse signals with the same pulse width, compared with the dual-threshold constant false alarm rate energy detection method, the DNLS method is improved by 15dB, 13dB and 4dB, respectively. Under actual data conditions, in the detection of CW-LFM pulse signals with the same pulse width, compared with the double-threshold constant false alarm rate energy detection method, the detection performance of the DNLS method in the case of no ship radiated noise interference and strong radiated noise interference improves by 5dB and 5.5dB, respectively. The data analysis results show that the DNLS method has very good detection performance for LFM, pulse trains of frequency modulated, CW-LFM and other sonar pulse signals at low SNR, and can effectively detect the sonar pulse signals under the background of strong ship radiated noise.

Background: The redirected jumping (RDJ) technique is a new locomotion method that saves physical tracking area and enhances the body movement experience of users in virtual reality. In a previous study, the range of imperceptible manipulation gains in RDJ was discussed in an empty virtual environment (VE). Methods: In this study, we conducted three tasks to investigate the influence of alley width on the detection threshold of jump redirection in a VE. Results: The results demonstrated that the imperceptible distance gain range in RDJ was not associated with the width of the alleys. The imperceptible height and rotation gain ranges in RDJ are related to the width of the alleys. Conclusions: We preliminarily summarized the relationship between the occlusion distance and manipulation range of the three gains in a complex environment. Simultaneously, the guiding principle for choosing three gains in RDJ according to the occlusion distance in a complex environment is provided.

Rapid advances in the development of sequencing technologies, numbers of commercial providers and diminishing costs have made DNA-based identification and diagnostics increasingly accessible to doctors and laboratories, eliminating the need for local investments in expensive technology and training or hiring of skilled technicians. However, reliable and comparable molecular analyses of bacteria in stool samples are dependent on storage and workflow conditions that do not introduce post-sampling bias, the most important factor being the need to keep the DNA at a stable detectable level. For that reason, there may remain other prohibitively costly requirements for cooling or freezing equipment or special chemical additives. This study investigates the diagnostic detectability of Salmonella and Campylobacter DNA in human, pig and chicken stool samples, stored at different temperatures and with different preservation methods. Stool samples were spiked with 106 CFU/mL of both Salmonella and Campylobacter strains stored at −20 °C, 5 °C and 20 °C (Room temperature, RT) and treated with either RNAlater, EDTA or Silica/ethanol. DNA was extracted at 9 different time points within 30 days and quantified by Qubit (total DNA) and qPCR (Salmonella and Campylobacter DNA). We found no statistically significant differences among the different preservation methods, and DNA from both species was easily detected at all time points and at all temperatures, both with and without preservation. This suggests that infections by these bacteria can be diagnosed and possibly also analysed in further detail simply by taking a stool sample in any suitable sealed container that can be transported to laboratory analysis without special storage or preservation requirements. We briefly discuss how this finding can benefit infection control in both developed and developing countries.

Magnetic beads improve biosensing performance by means of their small volume and controllability by magnetic force. In this study, a new technique composed of optically induced dielectrodphoresis (ODEP) manipulation and image processing was used to enhance the signal-to-noise ratio of the fluorescence for stained magnetic beads. According to natural advantages of size-dependent particle isolation by ODEP manipulation, biomarkers in clinical samples can be easily separated by different sizes of magnetic beads with corresponding captured antibodies, and rapidly distinguished by separated location of immunofluorescence. To verify the feasibility of the concept, magnetic beads with three different diameters, including 21.8, 8.7, and 4.2 μm, were easily separated and collected into specific patterns in the defined target zone treated as three dynamic transducer elements to evaluate fluorescence results. In magnetic beads with diameter of 4.2 μm, the lowest signal-to-noise ratio between stained and nonstained magnetic beads was 3.5. With the help of ODEP accumulation and detection threshold setting of 32, the signal-to-noise ratio was increased to 77.4, which makes this method more reliable. With the further optimization of specific antibodies immobilized on different-size magnetic beads in the future, this platform can be a potential candidate for a high-efficiency sensor array in clinical applications. [ABSTRACT FROM AUTHOR]

In this study, the spherical particle model and ten nonspherical particle models describing the scattering properties of snow are evaluated for potential use in precipitation estimation from spaceborne dual-frequency precipitation radar. The single scattering properties of nonspherical snow particles are computed using discrete dipole approximation (DDA), while those of spherical particles are determined using Mie theory. The precipitation profiles from WRF output are then input to a forward radiative transfer model to simulate the radar reflectivity at Ka-band and Ku-band. The results are validated with Global Precipitation Mission Dual-Frequency Precipitation Radar measurements. Greater consistency between the simulated and observed reflectivity is obtained when using the sector- and dendrite-shape assumptions. For the case in this study, when using the spherical-shape assumption, radar underestimates the error of the cloud’s top by about 300 m and underestimates the error of the cloud’s area by about 15%. As snowflake shapes change with temperature, we use the range between −40 °C and −5 °C to define three temperature layers. The relationships between reflectivity (Z) and precipitation rate (R) are fitted separately for the three layers, resulting in Z=134.59·R1.184 (sector) and Z=127.35·R1.221 (dendrite) below −40 °C.

Sleep deprivation has been shown to increase pain intensity and decrease pain thresholds in healthy subjects. In chronic pain patients, sleep impairment often worsens the perceived pain intensity. This increased pain perception is the result of altered nociceptive processing. We recently developed a method to quantify and monitor altered nociceptive processing by simultaneous tracking of psychophysical detection thresholds and recording of evoked cortical potentials during intra-epidermal electric stimulation. In this study, we assessed the sensitivity of nociceptive detection thresholds and evoked potentials to altered nociceptive processing after sleep deprivation in an exploratory study with 24 healthy male and 24 healthy female subjects. In each subject, we tracked nociceptive detection thresholds and recorded central evoked potentials in response to 180 single- and 180 double-pulse intra-epidermal electric stimuli. Results showed that the detection thresholds for single- and double-pulse stimuli and the average central evoked potential for single-pulse stimuli were significantly decreased after sleep deprivation. When analyzed separated by sex, these effects were only significant in the male population. Multivariate analysis showed that the decrease of central evoked potential was associated with a decrease of task-related evoked activity. Measurement repetition led to a decrease of the detection threshold to double-pulse stimuli in the mixed and the female population, but did not significantly affect any other outcome measures. These results suggest that simultaneous tracking of psychophysical detection thresholds and evoked potentials is a useful method to observe altered nociceptive processing after sleep deprivation, but is also sensitive to sex differences and measurement repetition. [ABSTRACT FROM AUTHOR]

Many widely used psychophysical olfactory tests have limitations that can create barriers to adoption. For example, tests that measure the ability to identify odors may confound sensory performance with memory recall, verbal ability, and prior experience with the odor. Conversely, classic threshold-based tests avoid these issues, but are labor intensive. Additionally, many commercially available tests are slow and may require a trained administrator, making them impractical for use in situations where time is at a premium or self-administration is required. We tested the performance of the Adaptive Olfactory Measure of Threshold (ArOMa-T)—a novel odor detection threshold test that employs an adaptive Bayesian algorithm paired with a disposable odorant delivery card—in a non-clinical sample of individuals (n = 534) at the 2021 Twins Day Festival in Twinsburg, OH. Participants successfully completed the test in under 3 min with a false alarm rate of 7.5% and a test–retest reliability of 0.61. Odor detection thresholds differed by sex (~3.2-fold lower for females) and age (~8.7-fold lower for the youngest versus the oldest age group), consistent with prior studies. In an exploratory analysis, we failed to observe evidence of detection threshold differences between participants who reported a history of COVID-19 and matched controls who did not. We also found evidence for broad-sense heritability of odor detection thresholds. Together, this study suggests the ArOMa-T can determine odor detection thresholds. Additional validation studies are needed to confirm the value of ArOMa-T in clinical or field settings where rapid and portable assessment of olfactory function is needed. [ABSTRACT FROM AUTHOR]

Global Navigation Satellite Systems (GNSS) spoofing is a pernicious type of intentional interference where a GNSS receiver is fooled into tracking counterfeit signals, with the purpose of inducing a misleading information into the application it is used for. A possible technique able to identify a GNSS spoofing attack is a dual-antenna method based on the analysis of the dispersion of the double differences (D3) of carrier-phase measurements. Such technique has been recently presented as a relatively simple method to detect situations where even only a subset of counterfeit signals is tracked by the receiver. However, the D3 technique has not been analyzed in a rigorous theoretical way so far and the detection threshold was, for instance, set only empirically. Aiming at filling these gaps, this article intends to revise the main concepts of the aforementioned technique in a clear mathematical way. Thus, the detection threshold will be given according to a target probability of missed detection. Moreover, the article provides a thorough analysis of expected performance in terms of probability of missed detection and probability of false alarm, addressing them first as pairwise probability, then as overall probability. The effect of the signal C/N0 ratio on these detection performances is analyzed. Methods to reduce the occurrence of events of false alarm are also discussed. Eventually, an assessment of performance of the ${{\rm{D}}^3}$ algorithm is evaluated through a set of tests that emulate real working conditions. [ABSTRACT FROM AUTHOR]

In cognitive radio networks spectrum sensing plays a vital role to identify the presence or absence of the primary user. In conventional spectrum sensing one secondary user will make a final decision regarding the availability of licensed spectrum. But Secondary user fail to make a correct detection about the presence of the primary user if he is in fading environment and it causes interference to the licensed users. Therefore to avoid interference to the licensed users and to make correct detection, number of samples is increased, Which increases the probability of detection. In this paper the optimization of samples is proposed to reduce the system overhead and also to increase the propagation time. Simulation results show the optimized value of samples for a given probability of false alarm and also the variation of probability of detection with optimized samples and false alarm is shown in the results. ABSTRAK: Dalam rangkaian radio kognitif, penginderaan spektrum memainkan peranan penting untuk mengenal pasti kehadiran atau ketiadaan pengguna utama. Dalam penginderaan spektrum konvensional, seorang pengguna sekunder akan membuat keputusan akhir mengenai ketersediaan spektrum berlesen. Tetapi pengguna Sekunder gagal membuat pengesanan yang betul mengenai kehadiran pengguna utama jika dia berada dalam persekitaran yang pudar dan menyebabkan gangguan kepada pengguna yang berlesen. Oleh itu untuk mengelakkan gangguan kepada pengguna berlesen dan membuat pengesanan yang betul, jumlah sampel meningkat, yang meningkatkan kemungkinan pengesanan. Dalam makalah ini pengoptimuman sampel dicadangkan untuk mengurangi overhead sistem dan juga untuk meningkatkan waktu penyebaran. Hasil simulasi menunjukkan nilai sampel yang dioptimumkan untuk kebarangkalian penggera palsu dan juga variasi kebarangkalian pengesanan dengan sampel yang dioptimumkan dan penggera palsu ditunjukkan dalam hasil.

Magnetic beads improve biosensing performance by means of their small volume and controllability by magnetic force. In this study, a new technique composed of optically induced dielectrodphoresis (ODEP) manipulation and image processing was used to enhance the signal-to-noise ratio of the fluorescence for stained magnetic beads. According to natural advantages of size-dependent particle isolation by ODEP manipulation, biomarkers in clinical samples can be easily separated by different sizes of magnetic beads with corresponding captured antibodies, and rapidly distinguished by separated location of immunofluorescence. To verify the feasibility of the concept, magnetic beads with three different diameters, including 21.8, 8.7, and 4.2 μm, were easily separated and collected into specific patterns in the defined target zone treated as three dynamic transducer elements to evaluate fluorescence results. In magnetic beads with diameter of 4.2 μm, the lowest signal-to-noise ratio between stained and nonstained magnetic beads was 3.5. With the help of ODEP accumulation and detection threshold setting of 32, the signal-to-noise ratio was increased to 77.4, which makes this method more reliable. With the further optimization of specific antibodies immobilized on different-size magnetic beads in the future, this platform can be a potential candidate for a high-efficiency sensor array in clinical applications.

Detection analyses are necessary to plan microseismic networks for use in the monitoring of anthropic activities. In 2014, the Italian Ministry of Economic Development (MiSE) issued guidelines for the monitoring of microseismic activity, ground deformations, and reservoir pore pressure. In 2016, the Istituto Nazionale di Geofisica e Vulcanologia (INGV) was commissioned to carry out specific investigations, aimed at assessing the guidelines applicability at the pilot site of the gas storage concession “Minerbio Stoccaggio” (Bologna). In this work, we present an overview of detection analysis, performed by the INGV team, during the experimental phase of the above mentioned guidelines. Measurements of ambient seismic noise, performed from 1 January 2018 to 31 March 2019, were used to assess detection thresholds of different configurations of the Minerbio Integrated Seismic Network (MISN). Detection analysis is particularly relevant for the Inner Domain of Detection (IDD), the crustal volume centred on the reservoir, within which it is vital to ensure the highest network performance. The results obtained in this work, validated through data recorded by the MISN during the analysed period, show that in the worst noise conditions observable in the area, the final configuration of the MISN enables localising ML ≥ 1.0 events occurring in the whole IDD, in line with the monitoring requirements prescribed by the guidelines. [ABSTRACT FROM AUTHOR]

Monitoring nociceptive processing is a current challenge due to a lack of objective measures. Recently, we developed a method for simultaneous tracking of psychophysical detection probability and brain evoked potentials in response to intra-epidermal stimulation. An exploratory investigation showed that we could quantify nociceptive system behavior by estimating the effect of stimulus properties on the evoked potential (EP). The goal in this work was to accurately measure nociceptive system behavior using this method in a large group of healthy subjects to identify the locations and latencies of EP components and the effect of single- and double-pulse stimuli with an inter-pulse interval of 10 or 40 ms on these EP components and detection probability. First, we observed the effect of filter settings and channel selection on the EP. Subsequently, we compared statistical models to assess correlation of EP and detection probability with stimulus properties, and quantified the effect of stimulus properties on both outcome measures through linear mixed regression. We observed lateral and central EP components in response to intra-epidermal stimulation. Detection probability and central EP components were positively correlated to the amplitude of each pulse, regardless of the inter-pulse interval, and negatively correlated to the trial number. Both central and lateral EP components also showed strong correlation with detection. These results show that both the observed EP and the detection probability reflect the various steps of processing of a nociceptive stimulus, including peripheral nerve fiber recruitment, central synaptic summation, and habituation to a repeated stimulus. [ABSTRACT FROM AUTHOR]

Olfactory habituation corresponds to a decreased behavioral or perceptual response to an odor after a prolonged exposure to this odor. Our aim was to investigate whether long-term olfactory habituation and its recovery are similar in young (<35 years old) and older adults (>50). Fifty-seven participants were recruited for a 5-week longitudinal study. They were exposed to one of the two odors (manzanate alpha [MA], irone alpha [IA]) for 2 weeks at home. Olfactory detection thresholds for both odors were measured before and after exposure. Results showed that the two age groups behaved similarly. The long-term exposure to an odor led to a temporary increase of its detection threshold (lower sensitivity to the odor). IA thresholds were more sensitive to the duration of exposure with the odor than MA thresholds. One week after termination of exposure, participants fully recovered and even became more sensitive to both odors. No cross-habituation was found between the two odors. Our findings highlight that long-term habituation is specific to the odor exposed, behaves the same in young and older adults, and is fully reversible in both age groups after 1 week. [ABSTRACT FROM AUTHOR]

Individuals with autism spectrum disorders (ASD) are impaired not only in social competencies but also in sensory perception, particularly olfaction. The olfactory ability of individuals with ASD has been examined in several psychophysical studies, but the results have been highly variable, which might be primarily due to methodological difficulties in the control of odor stimuli (e.g., the problem of lingering scents). In addition, the neural correlates of olfactory specificities in individuals with ASD remain largely unknown. To date, only one study has investigated this issue using functional magnetic resonance imaging (fMRI). The present study utilized a sophisticated method−a pulse ejection system−to present well-controlled odor stimuli to participants with ASD using an ASD-friendly application. With this advantageous system, we examined their odor detection, identification, and evaluation abilities and measured their brain activity evoked by odors using functional near-infrared spectroscopy (fNIRS). As the odor detection threshold (DT) of participants with ASD was highly variable, these participants were divided into two groups according to their DT: an ASD-Low DT group and an ASD-High DT group. Behavioral results showed that the ASD-High DT group had a significantly higher DT than the typically developing (control) group and the ASD-Low DT group, indicating their insensitivity to the tested odors. In addition, while there was no significant difference in the odor identification ability between groups, there was some discrepancy between the groups’ evaluations of odor pleasantness. The brain data identified, for the first time, that neural activity in the right dorsolateral prefrontal cortex (DLPFC) was significantly weaker in the ASD-High DT group than in the control group. Moreover, the strength of activity in the right DLPFC was negatively correlated with the DT. These findings suggest that participants with ASD have impairments in the higher-order function of olfactory processing, such as olfactory working memory and/or attention.

Analytical methods must be qualified as part of the method development lifecycle for product characterization of biotherapeutics. For higher order structure characterization methods, such as near ultraviolet circular dichroism spectroscopy, qualification is performed to determine the expected variability of the method and to establish criteria for analytical product comparability, reference standard qualification, and analytical similarity evaluations. Typical method qualifications require a single product to be tested across several days with multiple replicates, essential to establish a quantitative limit for future product evaluation studies, which may be burdensome with respect to time, instrumentation, and material requirements. In this note, a methodology is proposed to expedite the qualification process for the near ultraviolet circular dichroism spectroscopy method, decreasing the number of required qualification runs, in many cases, to just one for each product. The significant reduction in the number of assays for qualification is achieved by utilizing historical data that applies universally across products of variable classification, size, and test date. Despite their differences, the products exhibit comparable method performance when compared to a product-specific reference standard, and a universal detection threshold is established for application to future product evaluations that meet pre-determined method suitability criteria following a single verification run. [ABSTRACT FROM AUTHOR]

This article analyzes the electromagnetic and thermal behavior when insulation deteriorates, leading to short-circuit (SC) faults in a triple redundant 9-phase permanent magnet-assisted synchronous reluctance machine. It defines a critical insulation resistance at which the temperature in the faulted insulation region reaches the cut-through temperature of the insulation material and determines the minimum and maximum bounds of the critical resistance for all possible faulty insulation volumes by three-dimensional thermal analysis. It suggests insulation resistance thresholds for fault detection and mitigation action in order to prevent complete insulation failure with serious consequences. Moreover, an example is given to show that the insulation deterioration process may begin from large insulation resistance and is accelerated when the insulation material resistivity decreases with increase in temperature. Finally, tests on a prototype machine drive are performed to validate the predicted electromagnetic behavior under turn-to-turn insulation deterioration leading to SC faults. [ABSTRACT FROM AUTHOR]

It has been shown that assessment of the conditions and diagnostics of defects in asynchronous electric motors operating in various industrial installations can be carried out by analyzing the spectrograms of consumed current. The spectrograms were obtained using the diagnostic system of rotary machines (DSRM). A technique to determine the conditions and degree of development of defects in electric motors during their operation is considered; the technique is based on the identification of amplitudes of spectral components of the current spectrum of a working electric motor, which are typical for a specific defect, and comparison of the magnitude of amplitudes with the detection threshold of this defect. The results of diagnostics of defects and their development with time for specific electric motors, as well as the conditions of these electric motors after repairing, have been considered. [ABSTRACT FROM AUTHOR]

Sweet taste perception is a key factor in the establishment of the food pattern with nonstatic thresholds. Indeed, taste sensitivity can be influenced by physiological factors (age and sex), pathologies (obesity and type 2 diabetes mellitus), and acquired habits (tobacco and alcohol consumption). In order to elucidate how these variables influence the sucrose detection threshold (DT) and recognition threshold (RT), a systematic review and meta‐analysis of the relevant literature were performed. After a comprehensive search in the PubMed and Scopus databases, a total of 48 studies were qualitatively considered, and 44 were meta‐analyzed. The factors of aging (standard mean difference [SMD]: −0.46; 95% confidence interval (CI), −0.74 to −0.19; I2: 73%; Tau2: 0.18) and type 2 diabetes mellitus (SMD: 0.30; 95% CI, 0.06 to 0.55; I2: 0%; Tau2: 0.00) were found to significantly increase the sucrose RT, whereas the DT only increased in subjects with a higher body mass index (SMD: 0.58; 95% CI, 0.35 to 0.82; I2: 0%; Tau2: 0.00). No effects of sex and tobacco smoking were found, and associations with alcohol consumption could not be assessed, as it was included as a variable in only one study. Feasible mechanisms underlying changes in sucrose thresholds include the modulation of hormones involved in energy and body weight homeostasis, taste bud abundance, taste brain signaling, and the gut–brain axis. The present work provides insights into the variables that should be considered when assessing sweet taste sensitivity, discusses the mechanisms underlying differences in sweet taste, and highlights the need for further research in the field of personalized nutrition. [ABSTRACT FROM AUTHOR]

Individuals with autism spectrum disorders (ASD) are impaired not only in social competencies but also in sensory perception, particularly olfaction. The olfactory ability of individuals with ASD has been examined in several psychophysical studies, but the results have been highly variable, which might be primarily due to methodological difficulties in the control of odor stimuli (e.g., the problem of lingering scents). In addition, the neural correlates of olfactory specificities in individuals with ASD remain largely unknown. To date, only one study has investigated this issue using functional magnetic resonance imaging (fMRI). The present study utilized a sophisticated method−a pulse ejection system−to present well-controlled odor stimuli to participants with ASD using an ASD-friendly application. With this advantageous system, we examined their odor detection, identification, and evaluation abilities and measured their brain activity evoked by odors using functional near-infrared spectroscopy (fNIRS). As the odor detection threshold (DT) of participants with ASD was highly variable, these participants were divided into two groups according to their DT: an ASD-Low DT group and an ASD-High DT group. Behavioral results showed that the ASD-High DT group had a significantly higher DT than the typically developing (control) group and the ASD-Low DT group, indicating their insensitivity to the tested odors. In addition, while there was no significant difference in the odor identification ability between groups, there was some discrepancy between the groups' evaluations of odor pleasantness. The brain data identified, for the first time, that neural activity in the right dorsolateral prefrontal cortex (DLPFC) was significantly weaker in the ASD-High DT group than in the control group. Moreover, the strength of activity in the right DLPFC was negatively correlated with the DT. These findings suggest that participants with ASD have impairments in the higher-order function of olfactory processing, such as olfactory working memory and/or attention. [ABSTRACT FROM AUTHOR]

The Baumgarten explosion occurred on 12 December 2017 at a gas storage site about 30 km east of Vienna, Austria. Acoustic arrivals from this accidental surface explosion were detected at dozens of stations of the AlpArray seismic network to distances up to 150 km, mainly in easterly directions. Thus it was expected that the Hungarian infrasound array PSZI located about 230 km to the east-southeast of Baumgarten would detect this acoustic wave as well. Standard progressive multichannel correlation processing and frequency-wavenumber analysis identified a signal emerging at 7:57:55 UTC from an azimuth of 296°–300° and with trace-velocity > 400 m/s. The extraordinarily high trace-velocity and excessive backazimuth residual, relative to the explosion site direction of 282°, however cast strong doubts on the arrival's connection to the Baumgarten event. Accounting for the effect of non-planar geometry of the infrasound array results in a reduction of the azimuth residual by half. Additionally, 2D and 3D raytracing methods are used including the European Centre for Medium-Range Weather Forecasts (ECMWF) atmospheric model to further explain the remaining azimuth residual as well as to elucidate the large trace velocity estimates. The prevailing stratospheric winds in excess of 150 m/s are identified as the underlying cause. Including both factors the initial azimuth residual of up to 18° decreases to ~ 4°, allowing to associate the infrasound signal at PSZI with the Baumgarten event. Finally, the data from a seismic station at 30 km range is re-investigated for magnitude estimation. The local magnitude of ML < 1.0 explains well the scarcity of seismic observations within 50 km range, where three or four stations show signals, mainly consisting of Rg-type surface waves, but no body waves. [ABSTRACT FROM AUTHOR]

Introduction: The assessment of taste is critically important for an individual to enjoy life. This however, gets altered in various diseases. Diabetes Mellitus is one of the diseases in which person has dysgeusia. Objectives: This study was done to assess different taste sensations in patients suffering from Diabetes Mellitus Type II. Methods: A total of 120 subjects were taken in this study and were divided into 3 groups. One group consisted of patients who were uncontrolled diabetics (n = 40), the second group of controlled diabetics (n = 40) and 40 subjects who were normal healthy individuals (control group). To assess their gustatory functions, two tests were performed, whole mouth above threshold and localized taste test. Whole mouth above threshold test was performed by assessing their detection threshold for each taste. Results: It was seen that patients with Diabetes Mellitus showed a high threshold to sweet, salty and sour taste. Bitter was not affected in either of the groups. The other test performed was localized (spatial) test. In this test, various parts of the oral cavity are assessed by dabbing the highest concentration of the prepared solutions and their response is noted. The tongue was divided into Left posterior tongue (LPT), Right posterior tongue (RPT), Right Anterior tongue (RAT), Left Anterior tongue (LAT). Soft palate was divided into Right Soft Palate (RSP) and Left Soft Palate (LSP). The results showed a significant difference for the sweet taste in the localized regions (right anterior tongue [RAT], left anterior tongue [LAT], right posterior tongue [RPT], left posterior tongue [LPT], right soft palate [RSP], and left soft palate [LSP]) of the mouth between the three groups (P < 0.05). The results of the salty taste showed significant differences in the RAT, LAT, RSP, and LSP regions of the mouth between the groups (P < 0.05). However, the regions of LPT and RPT showed no differences between the study groups (P > 0.05).The results showed a significant difference in the sour taste in the localized regions of the mouth in all the study groups (P < 0.05). The results of the bitter taste showed significant differences in the regions of the mouth in all the three groups (P < 0.05). However, the region of LPT showed no differences between the study groups (P > 0.05). Conclusion: Within the limitation of this study, it was concluded that the diabetic patients had an increased satiation effect of sweet taste therefore they needed an increased quantity of sweet taste to be perceived. It was also significant for salty and sour taste, whereas bitter taste had no significance. Spatial taste test also showed differences in different regions of the tongue, soft palate. The left posterior tongue area showed no changes.

In order to clarify the risk management ability of the elderly in the daily life, a study was carried out, in which, 150 elderly and 105 young control panelists have been asked to detect and identify three smells which are serving as indices of food degradation, namely acetic acid, trimethylamine, and methyl mercaptan in order to determine the olfactory thresholds. The results revealed that the thresholds were all higher in the elderly, and that their sense of smell had deteriorated compared with the young. The threshold distribution in the elderly was more widespread for acetic acid, and the difference between the detection and the recognition thresholds was smaller compared with the young. Regarding trimethylamine, some old panelists could not detect the prepared sample with the largest density, so its spread could not be determined using only a simple sample average. In order to determine the spread, a data fitting method was introduced. Regarding methyl mercaptan the spread of the threshold distribution was more widespread compared with other smells, even in the young, and this tendency was clearer with the recognition threshold. It was also found that 76 % of the elderly did not notice any deterioration in their olfactory ability. [ABSTRACT FROM AUTHOR]

This study presents a new technique for power quality (PQ) disturbance detection. The technique focuses on voltage sags and interruptions that are related to various faults, i.e. transmission line, feeder, and transformer faults. A maximal overlap discrete wavelet transform‐based PQ detection algorithm is proposed to provide accurate points of disturbance initiation and recovery. The proposed PQ detection algorithm is robust even without a detection threshold and independent of the sampling frequency of PQ recording. In consideration of the presence of noise conditions, the preprocessed PQ waveforms are converted into 2D binary vectors using space vector transformation. Then, an improved stacked sparse denoising autoencoder combined with supervised backpropagation training is proposed as a robust classifier. Results show that the proposed method is suitable for detecting various types of PQ disturbances and possesses high recognition accuracy despite insufficient training samples. [ABSTRACT FROM AUTHOR]

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In practice, medium pulse repetition frequency (PRF) radar system is widely used as it takes both the advantages of low and high PRF radars. However, range and Doppler ambiguities appear in such a complicated system. Traditional target tracking algorithms first threshold raw measurements and obtain points from different PRF, then perform ambiguity resolutions over them to obtain the unambiguous measurements. It leads to a rather poor performance when target signal-to-noise ratio is low. While multi-frame track-before-detect (MF-TBD) is an advantageous method to track weak targets, but it fails to be applied in multiple PRF radar system directly. In this study, two algorithms based on MF-TBD are proposed. Classical ambiguity resolution (CAR) TBD first resolves ambiguities by means of a robust Chinese Remainder Theorem, where the first detection threshold is below the normal threshold, and then MF-TBD is applied for further tracking. The simulation shows that the proposed method significantly outperforms the CAR detect-before-track algorithm. [ABSTRACT FROM AUTHOR]

The constant false alarm rate (CFAR) technology plays an important role in radar target detection. In cell averaging CFAR detectors, a reference window is usually adopted to estimate the average interference power in the range–Doppler matrix and to obtain the detection threshold, which should be set high enough to limit false alarm rate to a tolerably small rate. The conventional rectangular window, cross window, and column window are investigated in this study, which may suffer from a degraded detection performance due to involving some extraneous reference cells. Therefore, a modified reference window for two-dimensional CFAR is proposed to improve performance, depending on the distribution characteristics of radar targets in range and Doppler dimensions. The experimental results demonstrate its performance advantages on detection probability, CFAR loss, and figure of merit. [ABSTRACT FROM AUTHOR]

The constant false alarm rate (CFAR) detection method based on multi-look polarisation whitening filter (MPWF) has not been obtained in the polarimetric synthetic aperture radar imagery when the texture variable obeys the Inverse Beta distribution. To solve the problem, a new CFAR detection method with analytical expression for false alarm rate is proposed. First, the probability density function (PDF) of the output via MPWF is derived based on the hypothesis of the texture variables obeying the Inverse Beta distribution in the product model. Secondly, the analytical expression of false alarm rate about detection threshold is obtained by integrating the PDF of MPWF output, and the procedure of the CFAR detection method is designed. Finally, the performance comparisons are made among the new method, Wishart CFAR detection algorithm and the two-parameter CFAR method via simulated and real data of AIRSAR. The results show that figure of merit of the new method is the highest and the new method gives the best performance in Inverse Beta distribution case. [ABSTRACT FROM AUTHOR]